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Raju S. Bapi
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- affiliation: University of Hyderabad, School of Computer and Information Sciences / Cognitive Science Lab, India
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2020 – today
- 2024
- [c75]Suvadeep Maiti, Shivam Kumar Sharma, Raju S. Bapi:
Enhancing Healthcare with EOG: A Novel Approach to Sleep Stage Classification. ICASSP 2024: 2305-2309 - [c74]Mehul Arora, Chirag Shantilal Jain, Lalith Bharadwaj Baru, Kamalaker Dadi, Raju S. Bapi:
HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable HyperEdges. IJCNN 2024: 1-8 - [i19]Mehul Arora, Chirag Shantilal Jain, Lalith Bharadwaj Baru, Kamalaker Dadi, Bapi Raju Surampudi:
HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable Hyperedges. CoRR abs/2403.14484 (2024) - 2023
- [c73]Subba Reddy Oota, Mounika Marreddy, Manish Gupta, Raju S. Bapi:
How does the brain process syntactic structure while listening? ACL (Findings) 2023: 6624-6647 - [c72]Rohan R. Donapati, Anuj Shukla, Raju Surampudi Bapi:
Intended Outcomes Expand In Time: Evidence from the Temporal Reproduction Task. CogSci 2023 - [c71]Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy, Manish Gupta, Raju S. Bapi:
Neural Architecture of Speech. ICASSP 2023: 1-5 - [c70]Dolton Fernandes, Pramod S. Kaushik, Raju Surampudi Bapi:
Emergence of Direction Selectivity and Motion Strength in Dot Motion Task Through Deep Reinforcement Learning Networks. IJCNN 2023: 1-7 - [c69]Pindi Krishna Chandra Prasad, Kamalaker Dadi, Bapi Raju Surampudi:
Dynamic functional connectivity analysis in individuals with Autism Spectrum Disorder. IJCNN 2023: 1-7 - [c68]Upadrasta Naga Sita Sravanthi, Kamalakar Dadi, Bapi Raju Surampudi, P. N. Sylaja, C. Kesavadas, Srijithesh PR, Rinta Paul:
Application of Graph Theoretic measures for assessing efficacy of Stroke Rehabilitation. IJCNN 2023: 1-9 - [c67]Gautham Venugopal, Bapi Surampudi Raju:
Modelling Grid Navigation Using Reinforcement Learning Linear Ballistic Accumulators. IJCNN 2023: 1-8 - [c66]Subba Reddy Oota, Veeral Agarwal, Mounika Marreddy, Manish Gupta, Raju S. Bapi:
Speech Taskonomy: Which Speech Tasks are the most Predictive of fMRI Brain Activity? INTERSPEECH 2023: 5167-5171 - [c65]Rakesh Sengupta, Surampudi Bapi Raju, Anindya Pattanayak:
Exploring Emergent Properties of Recurrent Neural Networks Using a Novel Energy Function Formalism. LOD (1) 2023: 303-317 - [c64]Praveen Kumar Vesapogu, Bapi Raju Surampudi:
Encoded Deep Vectors for Eukaryotic Exon Prediction. PReMI 2023: 835-843 - [i18]Subba Reddy Oota, Mounika Marreddy, Manish Gupta, Bapi Raju Surampudi:
Syntactic Structure Processing in the Brain while Listening. CoRR abs/2302.08589 (2023) - [i17]Subba Reddy Oota, Manish Gupta, Raju S. Bapi, Gaël Jobard, Frédéric Alexandre, Xavier Hinaut:
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey). CoRR abs/2307.10246 (2023) - [i16]Shivam Kumar Sharma, Suvadeep Maiti, S. Mythirayee, Srijithesh Rajendran, S. Bapi Raju:
Data-efficient Deep Learning Approach for Single-Channel EEG-Based Sleep Stage Classification with Model Interpretability. CoRR abs/2309.07156 (2023) - [i15]Suvadeep Maiti, Shivam Kumar Sharma, Raju S. Bapi:
Enhancing Healthcare with EOG: A Novel Approach to Sleep Stage Classification. CoRR abs/2310.03757 (2023) - [i14]Prantik Deb, Lalith Bharadwaj Baru, Kamalaker Dadi, Raju S. Bapi:
BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision. CoRR abs/2310.07060 (2023) - 2022
- [j30]Kushal Borkar, Anusha Chaturvedi, P. K. Vinod, Raju Surampudi Bapi:
Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI. Frontiers Comput. Neurosci. 16 (2022) - [c63]Kamalaker Dadi, Bapi Raju Surampudi:
Big Data in Cognitive Neuroscience: Opportunities and Challenges. BDA 2022: 16-30 - [c62]Subba Reddy Oota, Jashn Arora, Manish Gupta, Raju Surampudi Bapi, Mariya Toneva:
Deep Learning for Brain Encoding and Decoding. CogSci 2022 - [c61]Anuj Shukla, Raju Surampudi Bapi:
Relative Numerical Context Affects Temporal Processing. CogSci 2022 - [c60]Subba Reddy Oota, Jashn Arora, Manish Gupta, Raju S. Bapi:
Multi-view and Cross-view Brain Decoding. COLING 2022: 105-115 - [c59]Subba Reddy Oota, Jashn Arora, Vijay Rowtula, Manish Gupta, Raju S. Bapi:
Visio-Linguistic Brain Encoding. COLING 2022: 116-133 - [c58]Anirban Bandyopadhyay, Sayan Ghosh, Dipayan Biswas, Raju Surampudi Bapi, V. Srinivasa Chakravarthy:
A Phenomenological Deep Oscillatory Neural Network Model to Capture the Whole Brain Dynamics in Terms of BOLD Signal. ICONIP (2) 2022: 160-171 - [c57]P. L. Ammar Ahmed, Archi Yadav, Avinash Sharma, Raju S. Bapi:
Multiple Kernel Learning for Modeling Resting State EEG Connectomes using Structural Connectivity of the Brain. IJCNN 2022: 1-7 - [c56]Arpita Dash, Raju S. Bapi, Dipanjan Roy, P. K. Vinod:
Characterizing the Dynamic Reorganization in Healthy Ageing and Classification of Brain Age. IJCNN 2022: 1-7 - [c55]Subba Reddy Oota, Archi Yadav, Arpita Dash, Raju S. Bapi, Avinash Sharma:
Multiple GraphHeat Networks for Structural to Functional Brain Mapping. IJCNN 2022: 1-8 - [c54]Pindi Krishna Chandra Prasad, Yash Khare, Kamalaker Dadi, P. K. Vinod, Bapi Raju Surampudi:
Deep Learning Approach for Classification and Interpretation of Autism Spectrum Disorder. IJCNN 2022: 1-8 - [c53]Ekansh Chauhan, Swathi Guptha, Likith Reddy, Raju S. Bapi:
LRH-Net: A Multi-level Knowledge Distillation Approach for Low-Resource Heart Network. DeCaF/FAIR@MICCAI 2022: 190-201 - [c52]Vamsi Kumar, Likith Reddy, Shivam Kumar Sharma, Kamalaker Dadi, Chiranjeevi Yarra, Raju S. Bapi, Srijithesh Rajendran:
mulEEG: A Multi-view Representation Learning on EEG Signals. MICCAI (3) 2022: 398-407 - [c51]Subba Reddy Oota, Jashn Arora, Veeral Agarwal, Mounika Marreddy, Manish Gupta, Bapi Raju Surampudi:
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity? NAACL-HLT 2022: 3220-3237 - [e1]Raju S. Bapi, Sandeep S. Kulkarni, Swarup Mohalik, Sathya Peri:
Distributed Computing and Intelligent Technology - 18th International Conference, ICDCIT 2022, Bhubaneswar, India, January 19-23, 2022, Proceedings. Lecture Notes in Computer Science 13145, Springer 2022, ISBN 978-3-030-94875-7 [contents] - [i13]Pramod Kaushik, Sneha Kummetha, Perusha Moodley, Raju S. Bapi:
A Conservative Q-Learning approach for handling distribution shift in sepsis treatment strategies. CoRR abs/2203.13884 (2022) - [i12]Vamsi Kumar, Likith Reddy, Shivam Kumar Sharma, Kamalakar Dadi, Chiranjeevi Yarra, Raju S. Bapi, Srijithesh Rajendran:
mulEEG: A Multi-View Representation Learning on EEG Signals. CoRR abs/2204.03272 (2022) - [i11]Likith Reddy, Vivek Talwar, Shanmukh Alle, Raju S. Bapi, U. Deva Priyakumar:
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification. CoRR abs/2204.05116 (2022) - [i10]Ekansh Chauhan, Swathi Guptha, Likith Reddy, Raju S. Bapi:
LRH-Net: A Multi-Level Knowledge Distillation Approach for Low-Resource Heart Network. CoRR abs/2204.08000 (2022) - [i9]Subba Reddy Oota, Jashn Arora, Vijay Rowtula, Manish Gupta, Raju S. Bapi:
Visio-Linguistic Brain Encoding. CoRR abs/2204.08261 (2022) - [i8]Subba Reddy Oota, Jashn Arora, Manish Gupta, Raju S. Bapi:
Cross-view Brain Decoding. CoRR abs/2204.09564 (2022) - [i7]Subba Reddy Oota, Jashn Arora, Veeral Agarwal, Mounika Marreddy, Manish Gupta, Bapi Raju Surampudi:
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity? CoRR abs/2205.01404 (2022) - 2021
- [j29]Md. Qutubuddin, Tilahun Kochito Gibo, Raju S. Bapi, Narri Yadaiah:
Brain Affective System Inspired Control Architecture: An Application to Nonlinear System. IEEE Access 9: 86565-86580 (2021) - [c50]Likith Reddy, Vivek Talwar, Shanmukh Alle, Raju S. Bapi, U. Deva Priyakumar:
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification. SMC 2021: 1068-1074 - 2020
- [j28]John Eric Steephen, Siva C. Obbineni, Sneha Kummetha, Raju S. Bapi:
HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion. IEEE Trans. Affect. Comput. 11(4): 736-750 (2020) - [c49]Krishn Bera, Yash Mandilwar, Anuj Shukla, Raju S. Bapi:
Value-of-Information based Arbitration between Model-based and Model-free Control. CogSci 2020 - [c48]Krishn Bera, Anuj Shukla, Raju S. Bapi:
Motor Chunking During Sequence Learning in Grid-Navigation Tasks. CogSci 2020 - [c47]Krishn Bera, Anuj Shukla, Raju S. Bapi:
Grid-Navigation Tasks involve Skill Learning. CogSci 2020
2010 – 2019
- 2019
- [j27]Sriniwas Govinda Surampudi, Joyneel Misra, Gustavo Deco, Raju Surampudi Bapi, Avinash Sharma, Dipanjan Roy:
Resting state dynamics meets anatomical structure: Temporal multiple kernel learning (tMKL) model. NeuroImage 184: 609-620 (2019) - [c46]Subba Reddy Oota, Vijay Rowtula, Manish Gupta, Raju S. Bapi:
StepEncog: A Convolutional LSTM Autoencoder for Near-Perfect fMRI Encoding. IJCNN 2019: 1-8 - [c45]Preetam Srikar Dammu, Raju Surampudi Bapi:
Temporal Dynamics of the Brain Using Variational Bayes Hidden Markov Models: Application in Autism. PReMI (1) 2019: 121-130 - [c44]Preetam Srikar Dammu, Bapi Raju Surampudi:
Employing Temporal Properties of Brain Activity for Classifying Autism Using Machine Learning. PReMI (2) 2019: 193-200 - [i6]Krishn Bera, Tejas Savalia, S. Bapi Raju:
A Computational Framework for Motor Skill Acquisition. CoRR abs/1901.01856 (2019) - [i5]Subba Reddy Oota, Naresh Manwani, Raju S. Bapi:
ExpertoCoder: Capturing Divergent Brain Regions Using Mixture of Regression Experts. CoRR abs/1909.12299 (2019) - [i4]Krishn Bera, Yash Mandilwar, Raju S. Bapi:
Value-of-Information based Arbitration between Model-based and Model-free Control. CoRR abs/1912.05453 (2019) - 2018
- [j26]Vatika Harlalka, Raju S. Bapi, Palakkad Krishnan Unni Vinod, Dipanjan Roy:
Age, Disease, and Their Interaction Effects on Intrinsic Connectivity of Children and Adolescents in Autism Spectrum Disorder Using Functional Connectomics. Brain Connect. 8(7): 407-419 (2018) - [j25]Noor Pratap Singh, Raju S. Bapi, P. K. Vinod:
Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma. Comput. Biol. Medicine 100: 92-99 (2018) - [j24]Abobakr Khalil Alshamiri, Alok Singh, Bapi Raju Surampudi:
Two swarm intelligence approaches for tuning extreme learning machine. Int. J. Mach. Learn. Cybern. 9(8): 1271-1283 (2018) - [c43]Subba Reddy Oota, Naresh Manwani, Raju S. Bapi:
fMRI Semantic Category Decoding Using Linguistic Encoding of Word Embeddings. ICONIP (3) 2018: 3-15 - [i3]Subba Reddy Oota, Naresh Manwani, Raju S. Bapi:
fMRI Semantic Category Decoding using Linguistic Encoding of Word Embeddings. CoRR abs/1806.05177 (2018) - [i2]Subba Reddy Oota, Adithya Avvaru, Naresh Manwani, Raju S. Bapi:
Mixture of Regression Experts in fMRI Encoding. CoRR abs/1811.10740 (2018) - 2017
- [c42]Sneha Kummetha, Anuj Shukla, Raju S. Bapi:
Effects of Variable Response-Stimulus Interval (RSI) On Sequence Learning. CogSci 2017 - [c41]Remya Sankar, Anuj Shukla, Raju S. Bapi:
Experimental and Computational Investigation of the Effect of Caffeine on Human Time Perception. CogSci 2017 - [c40]Bhargav Teja Nallapu, Bapi Raju Surampudi, Nicolas P. Rougier:
The art of scaling up : A computational account on action selection in basal ganglia. IJCNN 2017: 52-58 - [c39]Pramod S. Kaushik, Maxime Carrere, Frédéric Alexandre, Surampudi Bapi Raju:
A biologically inspired neuronal model of reward prediction error computation. IJCNN 2017: 3577-3584 - [c38]Shruti Naik, Oota Subbareddy, Arpan Banerjee, Dipanjan Roy, Raju S. Bapi:
Metastability of cortical BOLD signals in maturation and senescence. IJCNN 2017: 4564-4570 - [c37]Gautam Malu, Raju S. Bapi, Bipin Indurkhya:
Learning Photography Aesthetics with Deep CNNs. MAICS 2017: 129-136 - [i1]Gautam Malu, Raju S. Bapi, Bipin Indurkhya:
Learning Photography Aesthetics with Deep CNNs. CoRR abs/1707.03981 (2017) - 2016
- [j23]Anirudh Nihalani Vattikonda, Bapi Raju Surampudi, Arpan Banerjee, Gustavo Deco, Dipanjan Roy:
Does the regulation of local excitation-inhibition balance aid in recovery of functional connectivity? A computational account. NeuroImage 136: 57-67 (2016) - [j22]Abobakr Khalil Alshamiri, Alok Singh, Bapi Raju Surampudi:
Artificial bee colony algorithm for clustering: an extreme learning approach. Soft Comput. 20(8): 3163-3176 (2016) - [c36]Jagadeeswara Rao Annam, Bapi Raju Surampudi:
AAMI Based ECG Heart-Beat Time-Series Clustering Using Unsupervised ELM and Decision Rule. ICIT 2016: 137-141 - [c35]Abobakr Khalil Alshamiri, Alok Singh, Bapi Raju Surampudi:
Comparative analysis of ELM and No-Prop algorithms. IC3 2016: 1-5 - 2015
- [j21]Pankaj Singh Dholaniya, Soumitra Ghosh, Bapi Raju Surampudi, Anand K. Kondapi:
A knowledge driven supervised learning approach to identify gene network of differentially up-regulated genes during neuronal senescence in Rattus norvegicus. Biosyst. 135: 9-14 (2015) - [j20]Kavita Vemuri, Bapi Raju Surampudi:
An Exploratory Investigation of Functional Network Connectivity of Empathy and Default Mode Networks in a Free-Viewing Task. Brain Connect. 5(6): 384-400 (2015) - 2014
- [j19]M. A. H. Farquad, Vadlamani Ravi, S. Bapi Raju:
Churn prediction using comprehensible support vector machine: An analytical CRM application. Appl. Soft Comput. 19: 31-40 (2014) - [j18]T. Maruthi Padmaja, Raju S. Bapi, Rudra N. Hota, P. Radha Krishna:
Class imbalance and its effect on PCA preprocessing. Int. J. Knowl. Eng. Soft Data Paradigms 4(3): 272-294 (2014) - [j17]Shesharao M. Wanjerkhede, Raju S. Bapi, Vithal D. Mytri:
Reinforcement learning and dopamine in the striatum: A modeling perspective. Neurocomputing 138: 27-40 (2014) - [c34]Krishna P. Miyapuram, Ujjval Pamnani, Kenji Doya, Raju S. Bapi:
Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning. ICONIP (1) 2014: 35-41 - [c33]Madhavi Alamuri, Bapi Raju Surampudi, Atul Negi:
A survey of distance/similarity measures for categorical data. IJCNN 2014: 1907-1914 - [c32]Komala Anamalamudi, Bapi Raju Surampudi, Madhavilatha Maganti:
Stochastic Leaky Integrator Model for Interval Timing. MIWAI 2014: 13-22 - [c31]Abobakr Khalil Alshamiri, Bapi Raju Surampudi, Alok Singh:
A Novel ELM K-Means Algorithm for Clustering. SEMCCO 2014: 212-222 - 2013
- [j16]T. Maruthi Padmaja, Raju S. Bapi, P. Radha Krishna:
A new probabilistic active sample selection algorithm for class imbalance problem. Int. J. Knowl. Eng. Soft Data Paradigms 4(1): 85-106 (2013) - [c30]Rakesh Sengupta, Anvita Gopal, Prajit Basu, David Melcher, Raju S. Bapi:
The influence of spatial cueing on serial order visual memory. CogSci 2013 - 2012
- [j15]Chandrasekhar V. S. Pammi, Krishna P. Miyapuram, Ahmed, Kazuyuki Samejima, Raju S. Bapi, Kenji Doya:
Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. NeuroImage 59(2): 1180-1189 (2012) - 2011
- [j14]Shesharao M. Wanjerkhede, Raju S. Bapi:
Role of CAMKII in reinforcement learning: a computational model of glutamate and dopamine signaling pathways. Biol. Cybern. 104(6): 397-424 (2011) - [j13]Mohammad Abdul Haque Farquad, Vadlamani Ravi, S. Bapi Raju:
Rule extraction from support vector machines: a hybrid approach for solving classification and regression problems. Int. J. Inf. Decis. Sci. 3(3): 265-294 (2011) - [c29]Mohammed Hussein Shukur, T. Sobha Rani, S. Durga Bhavani, G. Narahari Sastry, Surampudi Bapi Raju:
Local and Global Intrinsic Dimensionality Estimation for Better Chemical Space Representation. MIWAI 2011: 329-338 - [c28]B. Ravindra Reddy, T. Sobha Rani, S. Durga Bhavani, Raju S. Bapi, G. Narahari Sastry:
Correlating Binding Site Residues of the Protein and Ligand Features to Its Functionality. SEMCCO (2) 2011: 166-173 - 2010
- [j12]V. Srinivasa Chakravarthy, Denny Joseph, Raju S. Bapi:
What do the basal ganglia do? A modeling perspective. Biol. Cybern. 103(3): 237-253 (2010) - [j11]M. A. H. Farquad, Vadlamani Ravi, S. Bapi Raju:
Support vector regression based hybrid rule extraction methods for forecasting. Expert Syst. Appl. 37(8): 5577-5589 (2010) - [j10]Pradeep Kumar, Raju S. Bapi, P. Radha Krishna:
A New Similarity Metric for Sequential Data. Int. J. Data Warehous. Min. 6(4): 16-32 (2010) - [c27]T. Maruthi Padmaja, Raju S. Bapi, P. Radha Krishna:
A Class Specific Dimensionality Reduction Framework for Class Imbalance Problem: CPC_SMOTE. KDIR 2010: 237-242 - [c26]M. A. H. Farquad, Vadlamani Ravi, S. Bapi Raju:
Rule Extraction from Support Vector Machine Using Modified Active Learning Based Approach: An Application to CRM. KES (1) 2010: 461-470
2000 – 2009
- 2009
- [j9]T. Sobha Rani, Raju S. Bapi:
Analysis of n-Gram based Promoter Recognition Methods and Application to Whole Genome Promoter Prediction. Silico Biol. 9(1-2): S1-S16 (2009) - [c25]Shesharao M. Wanjerkhede, Raju S. Bapi:
A Computational study of pre-synaptic re-uptake of dopamine on phosphorylation of DARPP-32. IJCNN 2009: 3303-3310 - [c24]M. A. H. Farquad, Vadlamani Ravi, S. Bapi Raju:
Data Mining Using Rules Extracted from SVM: An Application to Churn Prediction in Bank Credit Cards. RSFDGrC 2009: 390-397 - 2008
- [j8]S. Durga Bhavani, T. Sobha Rani, Raju S. Bapi:
Feature selection using correlation fractal dimension: Issues and applications in binary classification problems. Appl. Soft Comput. 8(1): 555-563 (2008) - [j7]A. Srinivas Reddy, H. S. Durga Amarnath, Raju S. Bapi, G. Madhavi Sastry, G. Narahari Sastry:
Protein ligand interaction database (PLID). Comput. Biol. Chem. 32(5): 387-390 (2008) - [c23]T. Sobha Rani, Raju S. Bapi:
E.coli Promoter Recognition Through Wavelets. BIOCOMP 2008: 256-262 - [c22]T. Sobha Rani, Raju S. Bapi:
Cascaded Multi-level Promoter Recognition of E. coli Using Dinucleotide Features. ICIT 2008: 83-88 - 2007
- [j6]T. Sobha Rani, S. Durga Bhavani, Raju S. Bapi:
Analysis of E.coli promoter recognition problem in dinucleotide feature space. Bioinform. 23(5): 582-588 (2007) - [j5]Pradeep Kumar, P. Radha Krishna, Raju S. Bapi, Supriya Kumar De:
Rough clustering of sequential data. Data Knowl. Eng. 63(2): 183-199 (2007) - [j4]Pradeep Kumar, Raju S. Bapi, P. Radha Krishna:
SeqPAM: A Sequence Clustering Algorithm for Web Personalization. Int. J. Data Warehous. Min. 3(1): 29-53 (2007) - [c21]Sudhakara P. Reddy, Raju S. Bapi, Chakravarthy Bhagvati, Bulusu Lakshmana Deekshatulu:
Concept Pre-digestion Method for Image Relevance Reinforcement Learning. ICCTA 2007: 605-610 - [c20]Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Bapi:
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques. IJCAI 2007: 587-592 - [c19]Chaithanya Pichuka, Raju S. Bapi, Chakravarthy Bhagvati, Arun K. Pujari, Bulusu Lakshmana Deekshatulu:
A Tighter Error Bound for Decision Tree Learning Using PAC Learnability. IJCAI 2007: 1011-1016 - [c18]T. Maruthi Padmaja, Narendra Dhulipalla, P. Radha Krishna, Raju S. Bapi, Arijit Laha:
An Unbalanced Data Classification Model Using Hybrid Sampling Technique for Fraud Detection. PReMI 2007: 341-348 - 2006
- [j3]Raju S. Bapi, Krishna P. Miyapuram, F. X. Graydon, Kenji Doya:
fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. NeuroImage 32(2): 714-727 (2006) - [c17]T. Sobha Rani, S. Durga Bhavani, Raju S. Bapi:
Promoter Recognition using dinucleotide Features : A Case Study for E.Coli. ICIT 2006: 7-10 - [c16]Pradeep Kumar, Pisipati Radha Krishna, Raju S. Bapi, Supriya Kumar De:
Clustering using Similarity Upper Approximation. FUZZ-IEEE 2006: 839-844 - [c15]J. Naveen Kumar Reddy, Chakravarthy Bhagvati, Raju S. Bapi, Arun K. Pujari, Bulusu Lakshmana Deekshatulu:
Content Based Image Retrieval Using Region Labelling. ICVGIP 2006: 872-881 - [c14]Krishna P. Miyapuram, Raju S. Bapi, Chandrasekhar V. S. Pammi, Ahmed, Kenji Doya:
Hierarchical Chunking during Learning of Visuomotor Sequences. IJCNN 2006: 249-253 - [c13]Narri Yadaiah, Lakshman Singh, Raju S. Bapi, V. Seshagiri Rao, Bulusu Lakshmana Deekshatulu, Atul Negi:
MultisensorData Fusion Using Neural Networks. IJCNN 2006: 875-881 - 2005
- [c12]Pradeep Kumar, M. Venkateswara Rao, P. Radha Krishna, Raju S. Bapi:
Using Sub-sequence Information with kNN for Classification of Sequential Data. ICDCIT 2005: 536-546 - [c11]Pradeep Kumar, P. Radha Krishna, Supriya Kumar De, Raju S. Bapi:
Web Usage Mining Using Rough Agglomerative Clustering. ICEIS (2) 2005: 315-320 - [c10]Pradeep Kumar, M. Venkateswara Rao, P. Radha Krishna, Raju S. Bapi, Arijit Laha:
Intrusion Detection System Using Sequence and Set Preserving Metric. ISI 2005: 498-504 - 2004
- [c9]S. Kumar Chenna, Yogesh Kr. Jain, Himanshu Kapoor, Raju S. Bapi, Narri Yadaiah, Atul Negi, V. Seshagiri Rao, Bulusu Lakshmana Deekshatulu:
State Estimation and Tracking Problems: A Comparison Between Kalman Filter and Recurrent Neural Networks. ICONIP 2004: 275-281 - [c8]Chandrasekhar V. S. Pammi, Krishna P. Miyapuram, Raju S. Bapi, Kenji Doya:
Chunking Phenomenon in Complex Sequential Skill Learning in Humans. ICONIP 2004: 294-299 - 2003
- [c7]Anuj Kumar, Pramod Kumar Upadhyay, T. Sobha Rani, S. Durga Bhavani, Raju S. Bapi:
Identification of Promoter Region in a DNA Sequence Using EM Algorithm and Neural Networks. IICAI 2003: 676-684 - 2002
- [c6]Ahmed, Raju S. Bapi, Chandrasekhar V. S. Pammi, M. Krishna Prasad:
Application of Multilayer Perceptron Network for Tagging Parts-of-Speech. Language Engineering Conference 2002: 57 - 2001
- [c5]Raju S. Bapi, Kenji Doya:
Multiple Forward Model Architecture for Sequence Processing. Sequence Learning 2001: 308-320 - 2000
- [c4]John G. Taylor, Neill R. Taylor, Raju S. Bapi, Guido Bugmann, Daniel S. Levine:
The Frontal Lobes and Executive Function. IJCNN (1) 2000: 41-46
1990 – 1999
- 1998
- [c3]Raju S. Bapi, Kenji Doya:
A Sequence Learning Architecture Based on Cortico-Basal Ganglionic Loops and Reinforcement Learning. ICONIP 1998: 260-263 - 1997
- [j2]Raju S. Bapi, Brendan D'Cruz, Guido Bugmann:
Neuro-Resistive Grid Appraoch to Trainable Controllers: A Pole Balancing Example. Neural Comput. Appl. 5(1): 33-44 (1997) - [c2]Raju S. Bapi, Michael J. Denham:
Representational Issues in Neural Systems: Example from a Neural Network Model of Set-Shifting Paradigm Experiments. NCPW 1997: 129-141 - 1994
- [j1]Raju S. Bapi, Daniel S. Levine:
Modeling the role of frontal lobes in sequential task performance. I. Basic structure and primacy effects. Neural Networks 7(6-7): 1167-1180 (1994) - 1990
- [c1]Daniel S. Levine, Raju S. Bapi:
Networks modeling the involvement of the frontal lobes in learning and performance of flexible movement sequences. IJCNN 1990: 759-764
Coauthor Index
aka: Pisipati Radha Krishna
aka: Oota Subbareddy
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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 2024-09-21 01:47 CEST by the dblp team
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