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ORCIDMononito Goswami
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2020 – today
- 2024
[c18]Yifu Cai, Arvind Srinivasan, Mononito Goswami, Arjun Choudhry, Artur Dubrawski:
JoLT: Jointly Learned Representations of Language and Time-Series for Clinical Time-Series Interpretation (Student Abstract). AAAI 2024: 23447-23448- [c17]Eric Enouen, Sebastian Caldas, Mononito Goswami, Artur Dubrawski:
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract). AAAI 2024: 23482-23483 - [c16]Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski:
MOMENT: A Family of Open Time-series Foundation Models. ICML 2024 - [i14]Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski:
MOMENT: A Family of Open Time-series Foundation Models. CoRR abs/2402.03885 (2024) - [i13]Willa Potosnak, Cristian Challu, Mononito Goswami, Michal Wilinski, Nina Zukowska, Artur Dubrawski:
Implicit Reasoning in Deep Time Series Forecasting. CoRR abs/2409.10840 (2024) - [i12]Michal Wilinski, Mononito Goswami, Nina Zukowska, Willa Potosnak, Artur Dubrawski:
Unveiling and Manipulating Concepts in Time Series Foundation Models. CoRR abs/2409.12915 (2024) - [i11]Nina Zukowska, Mononito Goswami, Michal Wilinski, Willa Potosnak, Artur Dubrawski:
Towards Long-Context Time Series Foundation Models. CoRR abs/2409.13530 (2024) - 2023
- [c15]Mononito Goswami, Cristian I. Challu, Laurent Callot, Lenon Minorics, Andrey Kan:
Unsupervised Model Selection for Time Series Anomaly Detection. ICLR 2023 - [c14]Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski:
AQuA: A Benchmarking Tool for Label Quality Assessment. NeurIPS 2023 - [i10]Mononito Goswami, Vedant Sanil
, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit, Artur Dubrawski:
AQuA: A Benchmarking Tool for Label Quality Assessment. CoRR abs/2306.09467 (2023) - 2022
- [c13]Arnab Dey, Mononito Goswami, Joo Heung Yoon, Gilles Clermont, Michael R. Pinsky, Marilyn Hravnak, Artur Dubrawski:
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact. AMIA 2022 - [c12]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. KDD 2022: 3634-3644 - [c11]Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski:
Classifying Unstructured Clinical Notes via Automatic Weak Supervision. MLHC 2022: 673-690 - [i9]Mononito Goswami, Benedikt Boecking, Artur Dubrawski:
Weak Supervision for Affordable Modeling of Electrocardiogram Data. CoRR abs/2201.02936 (2022) - [i8]Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski:
Counterfactual Phenotyping with Censored Time-to-Events. CoRR abs/2202.11089 (2022) - [i7]Arnab Dey, Mononito Goswami, Joo Heung Yoon, Gilles Clermont, Michael R. Pinsky, Marilyn Hravnak, Artur Dubrawski:
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact. CoRR abs/2206.09074 (2022) - [i6]Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski:
Classifying Unstructured Clinical Notes via Automatic Weak Supervision. CoRR abs/2206.12088 (2022) - [i5]Mononito Goswami, Cristian Challu, Laurent Callot, Lenon Minorics, Andrey Kan:
Unsupervised Model Selection for Time-series Anomaly Detection. CoRR abs/2210.01078 (2022) - 2021
- [c10]Mononito Goswami, Benedikt Boecking, Artur Dubrawski:
Weak Supervision for Affordable Modeling of Electrocardiogram Data. AMIA 2021 - [i4]Chufan Gao, Mononito Goswami:
The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming. CoRR abs/2108.10921 (2021) - [i3]Saswati Ray, Sana Lakdawala, Mononito Goswami, Chufan Gao:
Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection. CoRR abs/2111.08082 (2021) - 2020
- [j2]Indu Singh, Minkush Manuja, Rishabh Mathur, Mononito Goswami:
Detecting intrusive transactions in databases using partially-ordered sequential rule mining and fractional-distance based anomaly detection. Int. J. Intell. Eng. Informatics 8(2): 138-171 (2020) - [j1]Ajay Kaushik, Mononito Goswami, Minkush Manuja, S. Indu, Daya Gupta:
A Binary PSO Approach for Improving the Performance of Wireless Sensor Networks. Wirel. Pers. Commun. 113(1): 263-297 (2020) - [c9]Mononito Goswami, Lujie Chen, Artur Dubrawski:
Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals. AAAI 2020: 420-427 - [c8]Mononito Goswami, Lujie Chen, Chufan Gao, Artur Dubrawski:
Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract). AAAI 2020: 13799-13800 - [c7]Minni Jain, Maitree Leekha, Mononito Goswami:
A Multi-Task Approach to Open Domain Suggestion Mining (Student Abstract). AAAI 2020: 13817-13818 - [c6]Rajni Jindal, Maitree Leekha, Minkush Manuja, Mononito Goswami:
What Makes a Better Companion? Towards Social & Engaging Peer Learning. ECAI 2020: 482-489 - [c5]Maitree Leekha, Mononito Goswami, Minni Jain:
A Multi-task Approach to Open Domain Suggestion Mining Using Language Model for Text Over-Sampling. ECIR (2) 2020: 223-229 - [c4]Andrew A. McReynolds, Sheba P. Naderzad, Mononito Goswami, Jack Mostow:
Toward Learning at Scale in Developing Countries: Lessons from the Global Learning XPRIZE Field Study. L@S 2020: 175-183 - [i2]Mononito Goswami, Minkush Manuja, Maitree Leekha:
Towards Social & Engaging Peer Learning: Predicting Backchanneling and Disengagement in Children. CoRR abs/2007.11346 (2020)
2010 – 2019
- 2019
- [c3]Mononito Goswami, Shiven Mian, Jack Mostow:
What's Most Broken? A Tool to Assist Data-Driven Iterative Improvement of an Intelligent Tutoring System. AAAI 2019: 9941-9942 - [c2]Shiven Mian, Mononito Goswami, Jack Mostow:
What's Most Broken? Design and Evaluation of a Tool to Guide Improvement of an Intelligent Tutor. AIED (1) 2019: 283-295 - [c1]Maitree Leekha, Mononito Goswami, Rajiv Ratn Shah, Yifang Yin, Roger Zimmermann:
Are You Paying Attention? Detecting Distracted Driving in Real-Time. BigMM 2019: 171-180 - [i1]Chufan Gao, Fabian Falck, Mononito Goswami, Anthony Wertz, Michael R. Pinsky, Artur Dubrawski:
Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning. CoRR abs/1911.05121 (2019)
Coauthor Index
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last updated on 2024-10-18 19:29 CEST by the dblp team
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