![](https://dblp.org/img/logo.ua.320x120.png)
![](https://dblp.org/img/dropdown.dark.16x16.png)
![](https://dblp.org/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.org/img/search.dark.16x16.png)
![search dblp](https://dblp.org/img/search.dark.16x16.png)
default search action
Lovekesh Vig
Person information
Refine list
![note](https://dblp.org/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c95]Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash, Sowmya Ramaswamy Krishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri:
Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback. AAAI 2024: 21-29 - [c94]Muskan Gupta
, Priyanka Gupta
, Jyoti Narwariya
, Lovekesh Vig
, Gautam Shroff
:
SCM4SR: Structural Causal Model-based Data Augmentation for Robust Session-based Recommendation. SIGIR 2024: 2609-2613 - [i71]Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Acceleron: A Tool to Accelerate Research Ideation. CoRR abs/2403.04382 (2024) - [i70]Shubham Paliwal, Arushi Jain, Monika Sharma, Vikram Jamwal, Lovekesh Vig:
CustomText: Customized Textual Image Generation using Diffusion Models. CoRR abs/2405.12531 (2024) - [i69]Arushi Jain, Shubham Paliwal, Monika Sharma, Vikram Jamwal, Lovekesh Vig:
Multi-Subject Personalization. CoRR abs/2405.12742 (2024) - [i68]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig, Gautam Shroff:
SmartFlow: Robotic Process Automation using LLMs. CoRR abs/2405.12842 (2024) - [i67]Pushpdeep Singh, Mayur Patidar, Lovekesh Vig:
Translating Across Cultures: LLMs for Intralingual Cultural Adaptation. CoRR abs/2406.14504 (2024) - 2023
- [c93]Mayur Patidar, Prayushi Faldu, Avinash Kumar Singh, Lovekesh Vig, Indrajit Bhattacharya, Mausam:
Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions. ACL (1) 2023: 10341-10357 - [c92]Amit Sangroya
, Suparshva Jain
, C. Anantaram
, Lovekesh Vig
:
Conceptual Explanations of ECG Classification using Large Language Models. AIMLSystems 2023: 59:1-59:3 - [c91]Shabbirhussain Bhaisaheb, Shubham Paliwal, Rajaswa Patil, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Program Synthesis for Complex QA on Charts via Probabilistic Grammar Based Filtered Iterative Back-Translation. EACL (Findings) 2023: 2456-2470 - [c90]Jyoti Narwariya, Priyanka Gupta, Garima Gupta, Lovekesh Vig, Gautam Shroff:
X4SR: Post-Hoc Explanations for Session-based Recommendations. eCom@SIGIR 2023 - [c89]Shubham Paliwal, Bhagyashree Gaikwad, Mayur Patidar, Manasi Patwardhan, Lovekesh Vig, Meghna Mahajan, Bagya Lakshmi V, Shirish S. Karande:
Ontology Guided Supervised Contrastive Learning For Fine-grained Attribute Extraction From Fashion Images. eCom@SIGIR 2023 - [c88]Soham Rohit Chitnis, Sidong Liu
, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva
, Shlomo Berkovsky
, Lovekesh Vig, Ashwin Srinivasan:
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. EMBC 2023: 1-4 - [c87]Shubham Paliwal, Manasi Patwardhan, Lovekesh Vig:
Generalization of Fine Granular Extractions from Charts. ICDAR (2) 2023: 94-110 - [c86]Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan
, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan:
IKD+: Reliable Low Complexity Deep Models for Retinopathy Classification. ICIP 2023: 2400-2404 - [c85]Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig:
Can LLMs solve generative visual analogies? IARML@IJCAI 2023: 30-32 - [c84]Jyotsana Khatri, Vivek Srivastava, Lovekesh Vig:
Can You Translate for Me? Code-Switched Machine Translation with Large Language Models. IJCNLP (2) 2023: 83-92 - [c83]Rishabh Patra, Ramya Hebbalaguppe, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. WACV 2023: 1541-1549 - [i66]S. I Harini, Gautam Shroff, Ashwin Srinivasan, Prayushi Faldu, Lovekesh Vig:
Neuro-symbolic Meta Reinforcement Learning for Trading. CoRR abs/2302.08996 (2023) - [i65]Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan:
Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification. CoRR abs/2302.09833 (2023) - [i64]Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan
, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan:
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification. CoRR abs/2303.02310 (2023) - [i63]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
Symbolic Regression for PDEs using Pruned Differentiable Programs. CoRR abs/2303.07009 (2023) - [i62]Ankita Sontakke, Kanika Kalra, Manasi Patwardhan, Lovekesh Vig, Raveendra Kumar Medicherla, Ravindra Naik, Shrishti Pradhan:
Knowledge Transfer for Pseudo-code Generation from Low Resource Programming Language. CoRR abs/2303.09062 (2023) - [i61]Ritam Majumdar, Shirish Karande, Lovekesh Vig:
DeepEpiSolver: Unravelling Inverse problems in Covid, HIV, Ebola and Disease Transmission. CoRR abs/2303.14194 (2023) - [i60]Krishnam Hasija, Shrishti Pradhan, Manasi Patwardhan, Raveendra Kumar Medicherla, Lovekesh Vig, Ravindra Naik:
Neuro-symbolic Zero-Shot Code Cloning with Cross-Language Intermediate Representation. CoRR abs/2304.13350 (2023) - [i59]Aseem Arora, Shabbirhussain Bhaisaheb, Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting. CoRR abs/2308.02582 (2023) - [i58]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
HyperLoRA for PDEs. CoRR abs/2308.09290 (2023) - [i57]Ritam Majumdar, Shirish Karande, Lovekesh Vig:
How important are specialized transforms in Neural Operators? CoRR abs/2308.09293 (2023) - [i56]Ritam Majumdar, Amey Varhade, Shirish S. Karande, Lovekesh Vig:
Can Physics Informed Neural Operators Self Improve? CoRR abs/2311.13885 (2023) - 2022
- [c82]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract). AAAI 2022: 13055-13056 - [c81]Manu Sheoran, Monika Sharma, Meghal Dani, Lovekesh Vig:
Handling Domain Shift for Lesion Detection via Semi-supervised Domain Adaptation. ACCV (Workshops) 2022: 102-116 - [c80]Amit Sangroya, Suparshva Jain, Lovekesh Vig, C. Anantaram, Arijit Ukil, Sundeep Khandelwal:
Generating Conceptual Explanations for DL based ECG Classification Model. FLAIRS 2022 - [c79]Manu Sheoran
, Meghal Dani, Monika Sharma, Lovekesh Vig:
An Efficient Anchor-Free Universal Lesion Detection in Ct-Scans. ISBI 2022: 1-4 - [c78]Vaibhav Varshney, Mayur Patidar, Rajat Kumar, Lovekesh Vig, Gautam Shroff:
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection. NAACL-HLT (Findings) 2022: 1113-1127 - [c77]Rajat Kumar, Mayur Patidar, Vaibhav Varshney, Lovekesh Vig, Gautam Shroff:
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering. NAACL-HLT 2022: 1836-1853 - [c76]Atharv Sonwane, Abhinav Lalwani, Sweta Mahajan, Gautam Shroff, Lovekesh Vig:
Neural Analogical Reasoning. NeSy 2022: 120-141 - [c75]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. NeSy 2022: 142-154 - [c74]Rajaswa Patil, Manasi Patwardhan, Shirish Karande, Lovekesh Vig, Gautam Shroff:
Exploring Dimensions of Generalizability and Few-shot Transfer for Text-to-SQL Semantic Parsing. TL4NLP 2022: 103-114 - [i55]Garima Gupta, Lovekesh Vig, Gautam Shroff:
DRTCI: Learning Disentangled Representations for Temporal Causal Inference. CoRR abs/2201.08137 (2022) - [i54]Jyoti Narwariya, Chetan Verma, Pankaj Malhotra, Lovekesh Vig, Easwar Subramanian, Sanjay Bhat:
Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs. CoRR abs/2202.05517 (2022) - [i53]Diksha Garg, Pankaj Malhotra, Anil Bhatia, Sanjay Bhat, Lovekesh Vig, Gautam Shroff:
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression. CoRR abs/2202.12578 (2022) - [i52]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. CoRR abs/2203.06852 (2022) - [i51]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words. CoRR abs/2203.06873 (2022) - [i50]Manu Sheoran
, Meghal Dani, Monika Sharma, Lovekesh Vig:
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection. CoRR abs/2203.06886 (2022) - [i49]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
An Efficient Anchor-free Universal Lesion Detection in CT-scans. CoRR abs/2203.16074 (2022) - [i48]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig:
On NeuroSymbolic Solutions for PDEs. CoRR abs/2207.06240 (2022) - [i47]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. CoRR abs/2209.08750 (2022) - [i46]Vedant Shah, Aditya Agrawal, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Tanmay T. Verlekar:
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss. CoRR abs/2211.16047 (2022) - [i45]Ramya Hebbalaguppe, Rishabh Patra, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. CoRR abs/2212.10005 (2022) - [i44]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs. CoRR abs/2212.10032 (2022) - [i43]Mayur Patidar, Avinash Kumar Singh, Prayushi Faldu, Lovekesh Vig, Indrajit Bhattacharya, Mausam:
Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions. CoRR abs/2212.10189 (2022) - 2021
- [j16]Kushal Veer Singh
, Ajay Kumar Verma
, Lovekesh Vig
:
Deep learning based network similarity for model selection. Data Sci. 4(2): 63-83 (2021) - [j15]Tirtharaj Dash
, Ashwin Srinivasan, Lovekesh Vig:
Incorporating symbolic domain knowledge into graph neural networks. Mach. Learn. 110(7): 1609-1636 (2021) - [c73]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection. BMVC 2021: 413 - [c72]Priyanka Gupta, Ankit Sharma, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
CauSeR: Causal Session-based Recommendations for Handling Popularity Bias. CIKM 2021: 3048-3052 - [c71]Arushi Jain, Shubham Paliwal
, Monika Sharma, Lovekesh Vig:
TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words. ESANN 2021 - [c70]Shruti Kunde, Amey Pandit, Kushagra Mahajan, Monika Sharma, Rekha Singhal, Lovekesh Vig:
Data-Efficient Training of High-Resolution Images in Medical Domain. ESANN 2021 - [c69]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. ICDM 2021: 161-170 - [c68]Manasi Malik, Garima Gupta, Lovekesh Vig, Gautam Shroff:
BCQ4DCA: Budget Constrained Deep Q-Network for Dynamic Campaign Allocation in Computational Advertising. IJCNN 2021: 1-8 - [c67]Shubham Paliwal, Monika Sharma, Lovekesh Vig:
OSSR-PID: One-Shot Symbol Recognition in P&ID Sheets using Path Sampling and GCN. IJCNN 2021: 1-8 - [c66]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy:
Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design. ILP 2021: 78-94 - [c65]Shubham Paliwal, Arushi Jain, Monika Sharma, Lovekesh Vig:
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams. PAKDD (Workshops) 2021: 168-180 - [i42]Shubham Paliwal, Arushi Jain, Monika Sharma, Lovekesh Vig:
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams. CoRR abs/2109.03794 (2021) - [i41]Shubham Paliwal, Monika Sharma, Lovekesh Vig:
OSSR-PID: One-Shot Symbol Recognition in P&ID Sheets using Path Sampling and GCN. CoRR abs/2109.03849 (2021) - [i40]Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems. CoRR abs/2110.09947 (2021) - [i39]Mrinal Rawat, Ramya Hebbalaguppe, Lovekesh Vig:
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation. CoRR abs/2111.00506 (2021) - [i38]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning. CoRR abs/2111.10361 (2021) - 2020
- [j14]Priyanka Gupta
, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis Using Deep Neural Networks. J. Heal. Informatics Res. 4(2): 112-137 (2020) - [j13]Ashwin Srinivasan
, Lovekesh Vig, Gautam Shroff:
Constructing generative logical models for optimisation problems using domain knowledge. Mach. Learn. 109(7): 1371-1392 (2020) - [c64]Nikhil Jaiswal, Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal, Lovekesh Vig:
Improving NMT via Filtered Back Translation. WAT@AAC/IJCNLPL 2020: 154-159 - [c63]Amit Sangroya, Mouli Rastogi, C. Anantaram, Lovekesh Vig:
Guided-LIME: Structured Sampling based Hybrid Approach towards Explaining Blackbox Machine Learning Models. CIKM (Workshops) 2020 - [c62]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. COMAD/CODS 2020: 28-36 - [c61]Nikita Goel, Monika Sharma, Lovekesh Vig:
Font-ProtoNet: Prototypical Network based Font Identification of Document Images in Low Data Regime. CVPR Workshops 2020: 2369-2376 - [c60]Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan:
Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. CVPR Workshops 2020: 2377-2385 - [c59]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Meta-DermDiagnosis: Few-Shot Skin Disease Identification using Meta-Learning. CVPR Workshops 2020: 3142-3151 - [c58]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. ESANN 2020: 25-30 - [c57]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Causal Attention Model for Multi-touch Attribution. ICDM (Workshops) 2020: 79-86 - [c56]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Vidya Vikas:
Capsule Based Neural Network Architecture to perform completeness check for Patent Eligibility Process. IJCNN 2020: 1-8 - [c55]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CD@KDD 2020: 39-61 - [c54]Himani Srivastava, Prerna Khurana, Saurabh Srivastava, Vaibhav Varshney, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Improved Question Answering using Domain Prediction. Converse@KDD 2020 - [c53]Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff:
CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. TIA@MICCAI 2020: 61-73 - [c52]Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
A Case Study of Transfer of Lesion-Knowledge. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 138-145 - [i37]Shubham Paliwal
, Vishwanath D, Rohit Rahul, Monika Sharma, Lovekesh Vig:
TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images. CoRR abs/2001.01469 (2020) - [i36]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. CoRR abs/2004.13446 (2020) - [i35]Jyoti Narwariya, Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Gautam Shroff:
Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation. CoRR abs/2006.16556 (2020) - [i34]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Handling Variable-Dimensional Time Series with Graph Neural Networks. CoRR abs/2007.00411 (2020) - [i33]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CoRR abs/2008.09858 (2020) - [i32]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig:
Incorporating Symbolic Domain Knowledge into Graph Neural Networks. CoRR abs/2010.13900 (2020) - [i31]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs/2012.08984 (2020) - [i30]Rishab Khincha, Soundarya Krishnan, Krishnan Guru-Murthy, Tirtharaj Dash, Lovekesh Vig, Ashwin Srinivasan:
Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays. CoRR abs/2012.10787 (2020) - [i29]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Casual Attention Model for Multi-touch Attribution. CoRR abs/2012.11403 (2020)
2010 – 2019
- 2019
- [j12]Sucheta Chauhan, Lovekesh Vig, Shandar Ahmad:
ECG anomaly class identification using LSTM and error profile modeling. Comput. Biol. Medicine 109: 14-21 (2019) - [j11]Sucheta Chauhan, Lovekesh Vig, Michele De Filippo De Grazia
, Maurizio Corbetta
, Shandar Ahmad, Marco Zorzi
:
A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images. Frontiers Neuroinformatics 13: 53 (2019) - [j10]Ashwin Srinivasan, Lovekesh Vig, Michael Bain:
Logical Explanations for Deep Relational Machines Using Relevance Information. J. Mach. Learn. Res. 20: 130:1-130:47 (2019) - [c51]Kaushal Paneri, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters. AAAI 2019: 10003-10004 - [c50]Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
From Monolingual to Multilingual FAQ Assistant using Multilingual Co-training. DeepLo@EMNLP-IJCNLP 2019: 115-123 - [c49]Arijit Ukil, Pankaj Malhotra, Soma Bandyopadhyay, Tulika Bose, Ishan Sahu, Ayan Mukherjee, Lovekesh Vig, Arpan Pal, Gautam Shroff:
Fusing Features based on Signal Properties and TimeNet for Time Series Classification. ESANN 2019 - [c48]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Character Keypoint-Based Homography Estimation in Scanned Documents for Efficient Information Extraction. CBDAR@ICDAR 2019: 25-30 - [c47]Shubham Singh Paliwal, Vishwanath D, Rohit Rahul, Monika Sharma, Lovekesh Vig:
TableNet: Deep Learning Model for End-to-end Table Detection and Tabular Data Extraction from Scanned Document Images. ICDAR 2019: 128-133 - [c46]Rohit Rahul, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
Automatic Information Extraction from Piping and Instrumentation Diagrams. ICPRAM 2019: 163-172 - [c45]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. IJCNN 2019: 1-8 - [c44]Monika Sharma, Shikha Gupta, Arindam Chowdhury, Lovekesh Vig:
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks. IJCNN 2019: 1-7 - [c43]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Hierarchical Capsule Based Neural Network Architecture for Sequence Labeling. IJCNN 2019: 1-8 - [c42]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. NeSy@IJCAI 2019 - [c41]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-Box Optimization. ECML/PKDD (2) 2019: 366-381 - [c40]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Sequence and Time Aware Neighborhood for Session-based Recommendations: STAN. SIGIR 2019: 1069-1072 - [i28]Monika Sharma, Abhishek Verma, Lovekesh Vig:
Learning to Clean: A GAN Perspective. CoRR abs/1901.11382 (2019) - [i27]Rohit Rahul, Shubham Paliwal
, Monika Sharma, Lovekesh Vig:
Automatic Information Extraction from Piping and Instrumentation Diagrams. CoRR abs/1901.11383 (2019) - [i26]Vishnu TV, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models. CoRR abs/1903.09795 (2019) - [i25]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks. CoRR abs/1904.00655 (2019) - [i24]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. CoRR abs/1904.12546 (2019) - [i23]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. CoRR abs/1906.02427 (2019) - [i22]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-box Optimization. CoRR abs/1907.06901 (2019) - [i21]Priyanka Gupta, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs/1909.04276 (2019) - [i20]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. CoRR abs/1909.07155 (2019) - [i19]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction. CoRR abs/1911.05870 (2019) - [i18]Monika Sharma, Shikha Gupta, Arindam Chowdhury, Lovekesh Vig:
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks. CoRR abs/1911.09375 (2019) - [i17]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population. CoRR abs/1912.03960 (2019) - 2018
- [c39]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. AAAI Workshops 2018: 699-705 - [c38]Rohit Rahul, Arindam Chowdhury, Animesh, Samarth Mittal, Lovekesh Vig:
Reading Industrial Inspection Sheets by Inferring Visual Relations. ACCV Workshops 2018: 159-173 - [c37]Monika Sharma, Abhishek Verma, Lovekesh Vig:
Learning to Clean: A GAN Perspective. ACCV Workshops 2018: 174-185 - [c36]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. ACCV Workshops 2018: 186-201 - [c35]Arindam Chowdhury, Lovekesh Vig:
An Efficient End-to-End Neural Model for Handwritten Text Recognition. BMVC 2018: 202 - [c34]Mayur Patidar, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
Automatic Conversational Helpdesk Solution using Seq2Seq and Slot-filling Models. CIKM 2018: 1967-1975 - [c33]Sakti Saurav, Pankaj Malhotra, Vishnu TV, Narendhar Gugulothu, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Online anomaly detection with concept drift adaptation using recurrent neural networks. COMAD/CODS 2018: 78-87 - [c32]Gaurav Garg, Srinidhi Hegde, Ramakrishna Perla, Varun Jain, Lovekesh Vig, Ramya Hebbalaguppe:
DrawInAir: A Lightweight Gestural Interface Based on Fingertip Regression. ECCV Workshops (6) 2018: 229-240 - [c31]Swati, Monika Sharma, Lovekesh Vig:
Automatic Classification of Low-Resolution Chromosomal Images. ECCV Workshops (6) 2018: 315-325 - [c30]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. ESANN 2018 - [c29]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Using Features From Pre-trained TimeNET For Clinical Predictions. KDH@IJCAI 2018: 38-44 - [c28]Monika Sharma, Swati, Lovekesh Vig:
Automatic Chromosome Classification using Deep Attention Based Sequence Learning of Chromosome Bands. IJCNN 2018: 1-8 - [c27]Tirtharaj Dash
, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King:
Large-Scale Assessment of Deep Relational Machines. ILP 2018: 22-37 - [c26]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN. KDD 2018: 433-442 - [i16]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. CoRR abs/1805.06664 (2018) - [i15]Ashwin Srinivasan, Lovekesh Vig, Michael Bain:
Logical Explanations for Deep Relational Machines Using Relevance Information. CoRR abs/1807.00595 (2018) - [i14]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks. CoRR abs/1807.01705 (2018) - [i13]Arindam Chowdhury, Lovekesh Vig:
An Efficient End-to-End Neural Model for Handwritten Text Recognition. CoRR abs/1807.07965 (2018) - [i12]Vishal Sunder, Lovekesh Vig, Arnab Chatterjee, Gautam Shroff:
Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learning. CoRR abs/1809.07066 (2018) - [i11]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information extraction from Document images via relation extraction and Natural Language. CoRR abs/1812.04377 (2018) - [i10]Rohit Rahul, Arindam Chowdhury, Animesh, Samarth Mittal, Lovekesh Vig:
Reading Industrial Inspection Sheets by Inferring Visual Relations. CoRR abs/1812.07104 (2018) - [i9]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. CoRR abs/1812.11158 (2018) - 2017
- [j9]Kushal Veer Singh, Lovekesh Vig:
Improved prediction of missing protein interactome links via anomaly detection. Appl. Netw. Sci. 2: 2 (2017) - [c25]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Hybrid BiLSTM-Siamese network for FAQ Assistance. CIKM 2017: 537-545 - [c24]Monika Sharma, Oindrila Saha, Anand Sriraman, Ramya Hebbalaguppe, Lovekesh Vig, Shirish Karande:
Crowdsourcing for Chromosome Segmentation and Deep Classification. CVPR Workshops 2017: 786-793 - [c23]Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension. EACL (1) 2017: 850-859 - [c22]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. ESANN 2017 - [c21]Swati, Gaurav Gupta, Mohit Yadav, Monika Sharma, Lovekesh Vig:
Siamese Networks for Chromosome Classification. ICCV Workshops 2017: 72-81 - [c20]Somdyuti Paul
, Lovekesh Vig:
Deterministic Policy Gradient Based Robotic Path Planning with Continuous Action Spaces. ICCV Workshops 2017: 725-733 - [c19]Gaurav Gupta, Swati, Monika Sharma, Lovekesh Vig:
Information Extraction from Hand-Marked Industrial Inspection Sheets. CBDAR@ICDAR 2017: 33-38 - [c18]Sunder Vishal, Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Information Bottleneck Inspired Method For Chat Text Segmentation. IJCNLP(1) 2017: 194-203 - [c17]Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma:
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. ILP 2017: 169-183 - [c16]Monika Sharma, Ramya Hebbalaguppe, Lovekesh Vig:
Pre-trained classifiers with One Shot Similarity for context aware face verification and identification. ISBA 2017: 1-7 - [i8]Karamjit Singh, Garima Gupta, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Deep Convolutional Neural Networks for Pairwise Causality. CoRR abs/1701.00597 (2017) - [i7]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. CoRR abs/1706.08838 (2017) - [i6]Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks. CoRR abs/1709.01073 (2017) - 2016
- [c15]Ankit Verma, Monika Sharma, Ramya Hebbalaguppe, Ehtesham Hassan, Lovekesh Vig:
Automatic Container Code Recognition via Spatial Transformer Networks and Connected Component Region Proposals. ICMLA 2016: 728-733 - [c14]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. ILP 2016: 120-131 - [c13]Ramakrishna Perla, Ehtesham Hassan, Ramya Hebbalaguppe, Monika Sharma, Gaurav Gupta, Lovekesh Vig, Geetika Sharma, Gautam Shroff:
An AR Inspection Framework: Feasibility Study with Multiple AR Devices. ISMAR Adjunct 2016: 221-226 - [c12]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. CoCo@NIPS 2016 - [i5]Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K. Sriram, Gautam Shroff:
ODE - Augmented Training Improves Anomaly Detection in Sensor Data from Machines. CoRR abs/1605.01534 (2016) - [i4]Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection. CoRR abs/1607.00148 (2016) - [i3]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia, Puneet Agarwal:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. CoRR abs/1608.01093 (2016) - [i2]Pankaj Malhotra, Vishnu TV, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder. CoRR abs/1608.06154 (2016) - [i1]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. CoRR abs/1612.06528 (2016) - 2015
- [j8]Manoj Agarwal, Nitin Agrawal
, Shikhar Sharma, Lovekesh Vig, Naveen Kumar:
Parallel multi-objective multi-robot coalition formation. Expert Syst. Appl. 42(21): 7797-7811 (2015) - [c11]Sucheta Chauhan, Lovekesh Vig:
Anomaly detection in ECG time signals via deep long short-term memory networks. DSAA 2015: 1-7 - [c10]Urminder Singh
, Sucheta Chauhan, A. Krishnamachari, Lovekesh Vig:
Ensemble of deep long short term memory networks for labelling origin of replication sequences. DSAA 2015: 1-7 - [c9]Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Long Short Term Memory Networks for Anomaly Detection in Time Series. ESANN 2015 - [c8]Ankit Verma, Ramya Hebbalaguppe, Lovekesh Vig, Swagat Kumar
, Ehtesham Hassan
:
Pedestrian Detection via Mixture of CNN Experts and Thresholded Aggregated Channel Features. ICCV Workshops 2015: 555-563 - 2014
- [j7]Manoj Agarwal, Naveen Kumar
, Lovekesh Vig:
Non-additive multi-objective robot coalition formation. Expert Syst. Appl. 41(8): 3736-3747 (2014) - 2011
- [j6]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A dual association model for the extinction of animal conditioning. Neurocomputing 74(17): 3531-3542 (2011) - [j5]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
A Neurocomputational Model for the Relation Between Hunger, Dopamine and Action Rate. J. Intell. Syst. 20(4): 373-393 (2011) - [j4]Manoj Agarwal, Lovekesh Vig, Naveen Kumar
:
Multiple Objective Robot Coalition Formation. J. Intell. Syst. 20(4): 395-413 (2011) - [j3]Ashish Gupta, Lovekesh Vig, David C. Noelle
:
A Cognitive Model for Generalization during Sequential Learning. J. Robotics 2011: 617613:1-617613:12 (2011) - [c7]Ashish Gupta, Lovekesh Vig:
A Dual Association Model for Acquisition and Extinction. AI*IA 2011: 139-150 - [c6]Manoj Agarwal, Lovekesh Vig, Naveen Kumar
:
Multi-objective Robot Coalition Formation for Non-additive Environments. ICIRA (1) 2011: 346-355 - [c5]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
MORCFA: A Multiple Objective Robot Coalition Formation Algorithm. IICAI 2011: 268-279 - [c4]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
On the relation between hunger, dopamine and action rate. IICAI 2011: 1601-1617
2000 – 2009
- 2009
- [c3]Lovekesh Vig, Julie A. Adams:
The Effect of Coalition Imbalance on Multi-Robot Teams. IICAI 2009: 603-615 - 2007
- [j2]Lovekesh Vig, Julie A. Adams:
Coalition Formation: From Software Agents to Robots. J. Intell. Robotic Syst. 50(1): 85-118 (2007) - 2006
- [j1]Lovekesh Vig, Julie A. Adams:
Multi-robot coalition formation. IEEE Trans. Robotics 22(4): 637-649 (2006) - [c2]Lovekesh Vig, Julie A. Adams:
Market-Based Multi-robot Coalition Formation. DARS 2006: 227-236 - 2005
- [c1]Lovekesh Vig, Julie A. Adams:
A Framework for Multi-Robot Coalition Formation. IICAI 2005: 347-363
Coauthor Index
aka: Shubham Singh Paliwal
![](https://dblp.org/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-05 20:21 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint