Networks modeling the involvement of the frontal lobes in learning and performance of flexible movement sequences. - Daniel S. Levine 001; Raju S. Bapi (IJCNN, 1990)

Modeling the role of frontal lobes in sequential task performance. I. Basic structure and primacy effects. - Raju S. Bapi; Daniel S. Levine 001 (Neural Networks, 1994)

Representational Issues in Neural Systems: Example from a Neural Network Model of Set-Shifting Paradigm Experiments. - Raju S. Bapi; Michael J. Denham (NCPW, 1997)

Neuro-Resistive Grid Appraoch to Trainable Controllers: A Pole Balancing Example. - Raju S. Bapi; Brendan D'Cruz; Guido Bugmann (Neural Comput. Appl., 1997)

A Sequence Learning Architecture Based on Cortico-Basal Ganglionic Loops and Reinforcement Learning. - Raju S. Bapi; Kenji Doya (ICONIP, 1998)

The Frontal Lobes and Executive Function. - John G. Taylor; Neill R. Taylor; Raju S. Bapi; Guido Bugmann; Daniel S. Levine 001 (IJCNN (1), 2000)

Multiple Forward Model Architecture for Sequence Processing. - Raju S. Bapi; Kenji Doya (Sequence Learning, 2001)

Application of Multilayer Perceptron Network for Tagging Parts-of-Speech. - Ahmed; Raju S. Bapi; Chandrasekhar V. S. Pammi; M. Krishna Prasad (Language Engineering Conference, 2002)

Identification of Promoter Region in a DNA Sequence Using EM Algorithm and Neural Networks. - Anuj Kumar; Pramod Kumar Upadhyay; T. Sobha Rani; S. Durga Bhavani; Raju S. Bapi (IICAI, 2003)

State Estimation and Tracking Problems: A Comparison Between Kalman Filter and Recurrent Neural Networks. - S. Kumar Chenna; Yogesh Kr. Jain; Himanshu Kapoor; Raju S. Bapi; Narri Yadaiah; Atul Negi; V. Seshagiri Rao; Bulusu Lakshmana Deekshatulu (ICONIP, 2004)

Chunking Phenomenon in Complex Sequential Skill Learning in Humans. - Chandrasekhar V. S. Pammi; Krishna P. Miyapuram; Raju S. Bapi; Kenji Doya (ICONIP, 2004)

Using Sub-sequence Information with kNN for Classification of Sequential Data. - Pradeep Kumar 001; M. Venkateswara Rao; P. Radha Krishna 001; Raju S. Bapi (ICDCIT, 2005)

Web Usage Mining Using Rough Agglomerative Clustering. - Pradeep Kumar 001; P. Radha Krishna 001; Supriya Kumar De; Raju S. Bapi (ICEIS (2), 2005)

Role of presynaptic reuptake on dopamine modulation of cortico-striatal activity in TD learning. - Shesharao M. Wanjerkhede; Raju S. Bapi (IJCNN, 2005)

Intrusion Detection System Using Sequence and Set Preserving Metric. - Pradeep Kumar 001; M. Venkateswara Rao; P. Radha Krishna 001; Raju S. Bapi; Arijit Laha (ISI, 2005)

Promoter Recognition using dinucleotide Features : A Case Study for E.Coli. - T. Sobha Rani; S. Durga Bhavani; Raju S. Bapi (ICIT, 2006)

Clustering using Similarity Upper Approximation. - Pradeep Kumar 001; Pisipati Radha Krishna; Raju S. Bapi; Supriya Kumar De (FUZZ-IEEE, 2006)

Content Based Image Retrieval Using Region Labelling. - J. Naveen Kumar Reddy; Chakravarthy Bhagvati; Raju S. Bapi; Arun K. Pujari; Bulusu Lakshmana Deekshatulu (ICVGIP, 2006)

Hierarchical Chunking during Learning of Visuomotor Sequences. - Krishna P. Miyapuram; Raju S. Bapi; Chandrasekhar V. S. Pammi; Ahmed; Kenji Doya (IJCNN, 2006)

MultisensorData Fusion Using Neural Networks. - Narri Yadaiah; Lakshman Singh; Raju S. Bapi; V. Seshagiri Rao; Bulusu Lakshmana Deekshatulu; Atul Negi (IJCNN, 2006)

fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. - Raju S. Bapi; Krishna P. Miyapuram; F. X. Graydon; Kenji Doya (NeuroImage, 2006)

Concept Pre-digestion Method for Image Relevance Reinforcement Learning. - Sudhakara P. Reddy; Raju S. Bapi; Chakravarthy Bhagvati; Bulusu Lakshmana Deekshatulu (ICCTA, 2007)

A Tighter Error Bound for Decision Tree Learning Using PAC Learnability. - Chaithanya Pichuka; Raju S. Bapi; Chakravarthy Bhagvati; Arun K. Pujari; Bulusu Lakshmana Deekshatulu (IJCAI, 2007)

Detection of Cognitive States from fMRI Data Using Machine Learning Techniques. - Vishwajeet Singh; Krishna P. Miyapuram; Raju S. Bapi (IJCAI, 2007)

An Unbalanced Data Classification Model Using Hybrid Sampling Technique for Fraud Detection. - T. Maruthi Padmaja; Narendra Dhulipalla; P. Radha Krishna 001; Raju S. Bapi; Arijit Laha (PReMI, 2007)

Analysis of E.coli promoter recognition problem in dinucleotide feature space. - T. Sobha Rani; S. Durga Bhavani; Raju S. Bapi (Bioinform., 2007)

Rough clustering of sequential data. - Pradeep Kumar 001; P. Radha Krishna 001; Raju S. Bapi; Supriya Kumar De (Data Knowl. Eng., 2007)

SeqPAM: A Sequence Clustering Algorithm for Web Personalization. - Pradeep Kumar 001; Raju S. Bapi; P. Radha Krishna 001 (Int. J. Data Warehous. Min., 2007)

E.coli Promoter Recognition Through Wavelets. - T. Sobha Rani; Raju S. Bapi (BIOCOMP, 2008)

Cascaded Multi-level Promoter Recognition of E. coli Using Dinucleotide Features. - T. Sobha Rani; Raju S. Bapi (ICIT, 2008)

Feature selection using correlation fractal dimension: Issues and applications in binary classification problems. - S. Durga Bhavani; T. Sobha Rani; Raju S. Bapi (Appl. Soft Comput., 2008)

Protein ligand interaction database (PLID). - A. Srinivas Reddy; H. S. Durga Amarnath; Raju S. Bapi; G. Madhavi Sastry; G. Narahari Sastry (Comput. Biol. Chem., 2008)

A Computational study of pre-synaptic re-uptake of dopamine on phosphorylation of DARPP-32. - Shesharao M. Wanjerkhede; Raju S. Bapi (IJCNN, 2009)

Data Mining Using Rules Extracted from SVM: An Application to Churn Prediction in Bank Credit Cards. - M. A. H. Farquad; Vadlamani Ravi; S. Bapi Raju (RSFDGrC, 2009)

Analysis of n-Gram based Promoter Recognition Methods and Application to Whole Genome Promoter Prediction. - T. Sobha Rani; Raju S. Bapi (Silico Biol., 2009)

A Class Specific Dimensionality Reduction Framework for Class Imbalance Problem: CPC_SMOTE. - T. Maruthi Padmaja; Raju S. Bapi; P. Radha Krishna 001 (KDIR, 2010)

Rule Extraction from Support Vector Machine Using Modified Active Learning Based Approach: An Application to CRM. - M. A. H. Farquad; Vadlamani Ravi; S. Bapi Raju (KES (1), 2010)

What do the basal ganglia do? A modeling perspective. - V. Srinivasa Chakravarthy; Denny Joseph; Raju S. Bapi (Biol. Cybern., 2010)

Support vector regression based hybrid rule extraction methods for forecasting. - M. A. H. Farquad; Vadlamani Ravi; S. Bapi Raju (Expert Syst. Appl., 2010)

A New Similarity Metric for Sequential Data. - Pradeep Kumar 001; Raju S. Bapi; P. Radha Krishna 001 (Int. J. Data Warehous. Min., 2010)

Local and Global Intrinsic Dimensionality Estimation for Better Chemical Space Representation. - Mohammed Hussein Shukur; T. Sobha Rani; S. Durga Bhavani; G. Narahari Sastry; Surampudi Bapi Raju (MIWAI, 2011)

Correlating Binding Site Residues of the Protein and Ligand Features to Its Functionality. - B. Ravindra Reddy; T. Sobha Rani; S. Durga Bhavani; Raju S. Bapi; G. Narahari Sastry (SEMCCO (2), 2011)

Role of CAMKII in reinforcement learning: a computational model of glutamate and dopamine signaling pathways. - Shesharao M. Wanjerkhede; Raju S. Bapi (Biol. Cybern., 2011)

Rule extraction from support vector machines: a hybrid approach for solving classification and regression problems. - Mohammad Abdul Haque Farquad; Vadlamani Ravi; S. Bapi Raju (Int. J. Inf. Decis. Sci., 2011)

Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. - Chandrasekhar V. S. Pammi; Krishna P. Miyapuram; Ahmed; Kazuyuki Samejima; Raju S. Bapi; Kenji Doya (NeuroImage, 2012)

The influence of spatial cueing on serial order visual memory. - Rakesh Sengupta; Anvita Gopal; Prajit Basu; David Melcher; Raju S. Bapi (CogSci, 2013)

A new probabilistic active sample selection algorithm for class imbalance problem. - T. Maruthi Padmaja; Raju S. Bapi; P. Radha Krishna 001 (Int. J. Knowl. Eng. Soft Data Paradigms, 2013)

Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning. - Krishna P. Miyapuram; Ujjval Pamnani; Kenji Doya; Raju S. Bapi (ICONIP (1), 2014)

A survey of distance/similarity measures for categorical data. - Madhavi Alamuri; Bapi Raju Surampudi; Atul Negi (IJCNN, 2014)

Stochastic Leaky Integrator Model for Interval Timing. - Komala Anamalamudi; Bapi Raju Surampudi; Madhavilatha Maganti (MIWAI, 2014)

A Novel ELM K-Means Algorithm for Clustering. - Abobakr Khalil Alshamiri; Bapi Raju Surampudi; Alok Singh 001 (SEMCCO, 2014)

Churn prediction using comprehensible support vector machine: An analytical CRM application. - M. A. H. Farquad; Vadlamani Ravi; S. Bapi Raju (Appl. Soft Comput., 2014)

Class imbalance and its effect on PCA preprocessing. - T. Maruthi Padmaja; Raju S. Bapi; Rudra N. Hota; P. Radha Krishna 001 (Int. J. Knowl. Eng. Soft Data Paradigms, 2014)

Reinforcement learning and dopamine in the striatum: A modeling perspective. - Shesharao M. Wanjerkhede; Raju S. Bapi; Vithal D. Mytri (Neurocomputing, 2014)

A knowledge driven supervised learning approach to identify gene network of differentially up-regulated genes during neuronal senescence in Rattus norvegicus. - Pankaj Singh Dholaniya; Soumitra Ghosh; Bapi Raju Surampudi; Anand K. Kondapi (Biosyst., 2015)

An Exploratory Investigation of Functional Network Connectivity of Empathy and Default Mode Networks in a Free-Viewing Task. - Kavita Vemuri; Bapi Raju Surampudi (Brain Connect., 2015)

AAMI Based ECG Heart-Beat Time-Series Clustering Using Unsupervised ELM and Decision Rule. - Jagadeeswara Rao Annam; Bapi Raju Surampudi (ICIT, 2016)

Comparative analysis of ELM and No-Prop algorithms. - Abobakr Khalil Alshamiri; Alok Singh 001; Bapi Raju Surampudi (IC3, 2016)

Does the regulation of local excitation-inhibition balance aid in recovery of functional connectivity? A computational account. - Anirudh Nihalani Vattikonda; Bapi Raju Surampudi; Arpan Banerjee; Gustavo Deco; Dipanjan Roy (NeuroImage, 2016)

Artificial bee colony algorithm for clustering: an extreme learning approach. - Abobakr Khalil Alshamiri; Alok Singh 001; Bapi Raju Surampudi (Soft Comput., 2016)

Effects of Variable Response-Stimulus Interval (RSI) On Sequence Learning. - Sneha Kummetha; Anuj Shukla; Raju S. Bapi (CogSci, 2017)

Experimental and Computational Investigation of the Effect of Caffeine on Human Time Perception. - Remya Sankar; Anuj Shukla; Raju S. Bapi (CogSci, 2017)

A biologically inspired neuronal model of reward prediction error computation. - Pramod S. Kaushik; Maxime Carrere; Frédéric Alexandre; Surampudi Bapi Raju (IJCNN, 2017)

Metastability of cortical BOLD signals in maturation and senescence. - Shruti Naik; Oota Subbareddy; Arpan Banerjee; Dipanjan Roy; Raju S. Bapi (IJCNN, 2017)

The art of scaling up : A computational account on action selection in basal ganglia. - Bhargav Teja Nallapu; Bapi Raju Surampudi; Nicolas P. Rougier (IJCNN, 2017)

Learning Photography Aesthetics with Deep CNNs. - Gautam Malu; Raju S. Bapi; Bipin Indurkhya (MAICS, 2017)

fMRI Semantic Category Decoding Using Linguistic Encoding of Word Embeddings. - Subba Reddy Oota; Naresh Manwani; Raju S. Bapi (ICONIP (3), 2018)

Age, Disease, and Their Interaction Effects on Intrinsic Connectivity of Children and Adolescents in Autism Spectrum Disorder Using Functional Connectomics. - Vatika Harlalka; Raju S. Bapi; Palakkad Krishnan Unni Vinod; Dipanjan Roy (Brain Connect., 2018)

Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma. - Noor Pratap Singh; Raju S. Bapi; P. K. Vinod (Comput. Biol. Medicine, 2018)

Mixture of Regression Experts in fMRI Encoding. - Subba Reddy Oota; Adithya Avvaru; Naresh Manwani; Raju S. Bapi (CoRR, 2018)

Two swarm intelligence approaches for tuning extreme learning machine. - Abobakr Khalil Alshamiri; Alok Singh 001; Bapi Raju Surampudi (Int. J. Mach. Learn. Cybern., 2018)

StepEncog: A Convolutional LSTM Autoencoder for Near-Perfect fMRI Encoding. - Subba Reddy Oota; Vijay Rowtula; Manish Gupta 001; Raju S. Bapi (IJCNN, 2019)

Temporal Dynamics of the Brain Using Variational Bayes Hidden Markov Models: Application in Autism. - Preetam Srikar Dammu; Raju Surampudi Bapi (PReMI (1), 2019)

Employing Temporal Properties of Brain Activity for Classifying Autism Using Machine Learning. - Preetam Srikar Dammu; Bapi Raju Surampudi (PReMI (2), 2019)

A Computational Framework for Motor Skill Acquisition. - Krishn Bera; Tejas Savalia; S. Bapi Raju (CoRR, 2019)

ExpertoCoder: Capturing Divergent Brain Regions Using Mixture of Regression Experts. - Subba Reddy Oota; Naresh Manwani; Raju S. Bapi (CoRR, 2019)

Value-of-Information based Arbitration between Model-based and Model-free Control. - Krishn Bera; Yash Mandilwar; Raju S. Bapi (CoRR, 2019)

Resting state dynamics meets anatomical structure: Temporal multiple kernel learning (tMKL) model. - Sriniwas Govinda Surampudi; Joyneel Misra; Gustavo Deco; Raju Surampudi Bapi; Avinash Sharma 001; Dipanjan Roy (NeuroImage, 2019)

Value-of-Information based Arbitration between Model-based and Model-free Control. - Krishn Bera; Yash Mandilwar; Anuj Shukla; Raju S. Bapi (CogSci, 2020)

Motor Chunking During Sequence Learning in Grid-Navigation Tasks. - Krishn Bera; Anuj Shukla; Raju S. Bapi (CogSci, 2020)

Grid-Navigation Tasks involve Skill Learning. - Krishn Bera; Anuj Shukla; Raju S. Bapi (CogSci, 2020)

HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion. - John Eric Steephen; Siva C. Obbineni; Sneha Kummetha; Raju S. Bapi (IEEE Trans. Affect. Comput., 2020)

IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification. - Likith Reddy; Vivek Talwar; Shanmukh Alle; Raju S. Bapi; U. Deva Priyakumar (SMC, 2021)

Brain Affective System Inspired Control Architecture: An Application to Nonlinear System. - Md. Qutubuddin; Tilahun Kochito Gibo; Raju S. Bapi; Narri Yadaiah (IEEE Access, 2021)

Big Data in Cognitive Neuroscience: Opportunities and Challenges. - Kamalaker Dadi; Bapi Raju Surampudi (BDA, 2022)

Deep Learning for Brain Encoding and Decoding. - Subba Reddy Oota; Jashn Arora; Manish Gupta 001; Raju Surampudi Bapi; Mariya Toneva (CogSci, 2022)

Relative Numerical Context Affects Temporal Processing. - Anuj Shukla; Raju Surampudi Bapi (CogSci, 2022)

Multi-view and Cross-view Brain Decoding. - Subba Reddy Oota; Jashn Arora; Manish Gupta 001; Raju S. Bapi (COLING, 2022)

Visio-Linguistic Brain Encoding. - Subba Reddy Oota; Jashn Arora; Vijay Rowtula; Manish Gupta 001; Raju S. Bapi (COLING, 2022)

A Phenomenological Deep Oscillatory Neural Network Model to Capture the Whole Brain Dynamics in Terms of BOLD Signal. - Anirban Bandyopadhyay; Sayan Ghosh; Dipayan Biswas; Raju Surampudi Bapi; V. Srinivasa Chakravarthy (ICONIP (2), 2022)

Multiple Kernel Learning for Modeling Resting State EEG Connectomes using Structural Connectivity of the Brain. - P. L. Ammar Ahmed; Archi Yadav; Avinash Sharma 001; Raju S. Bapi (IJCNN, 2022)

Characterizing the Dynamic Reorganization in Healthy Ageing and Classification of Brain Age. - Arpita Dash; Raju S. Bapi; Dipanjan Roy; P. K. Vinod (IJCNN, 2022)

Multiple GraphHeat Networks for Structural to Functional Brain Mapping. - Subba Reddy Oota; Archi Yadav; Arpita Dash; Raju S. Bapi; Avinash Sharma 001 (IJCNN, 2022)

Deep Learning Approach for Classification and Interpretation of Autism Spectrum Disorder. - Pindi Krishna Chandra Prasad; Yash Khare; Kamalaker Dadi; P. K. Vinod; Bapi Raju Surampudi (IJCNN, 2022)

LRH-Net: A Multi-level Knowledge Distillation Approach for Low-Resource Heart Network. - Ekansh Chauhan; Swathi Guptha; Likith Reddy; Raju S. Bapi (DeCaF/FAIR@MICCAI, 2022)

mulEEG: A Multi-view Representation Learning on EEG Signals. - Vamsi Kumar; Likith Reddy; Shivam Kumar Sharma; Kamalaker Dadi; Chiranjeevi Yarra; Raju S. Bapi; Srijithesh Rajendran (MICCAI (3), 2022)

Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity? - Subba Reddy Oota; Jashn Arora; Veeral Agarwal; Mounika Marreddy; Manish Gupta 001; Bapi Raju Surampudi (NAACL-HLT, 2022)

A Conservative Q-Learning approach for handling distribution shift in sepsis treatment strategies. - Pramod Kaushik; Sneha Kummetha; Perusha Moodley; Raju S. Bapi (CoRR, 2022)

mulEEG: A Multi-View Representation Learning on EEG Signals. - Vamsi Kumar; Likith Reddy; Shivam Kumar Sharma; Kamalakar Dadi; Chiranjeevi Yarra; Raju S. Bapi; Srijithesh Rajendran (CoRR, 2022)

Cross-view Brain Decoding. - Subba Reddy Oota; Jashn Arora; Manish Gupta 001; Raju S. Bapi (CoRR, 2022)

Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI. - Kushal Borkar; Anusha Chaturvedi; P. K. Vinod; Raju Surampudi Bapi (Frontiers Comput. Neurosci., 2022)

How does the brain process syntactic structure while listening? - Subba Reddy Oota; Mounika Marreddy; Manish Gupta 001; Raju S. Bapi (ACL (Findings), 2023)

BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision. - Prantik Deb; Lalith Bharadwaj Baru; Kamalaker Dadi; Raju S. Bapi (BrainLes/SWITCH@MICCAI, 2023)

Intended Outcomes Expand In Time: Evidence from the Temporal Reproduction Task. - Rohan R. Donapati; Anuj Shukla; Raju Surampudi Bapi (CogSci, 2023)

Neural Architecture of Speech. - Subba Reddy Oota; Khushbu Pahwa; Mounika Marreddy; Manish Gupta 001; Raju S. Bapi (ICASSP, 2023)

A Comparative Study of Machine Learning Approaches for the Detection of SARS-CoV-2 and its Variants. - Praveen Kumar Vesapogu; Bapi Raju Surampudi (ICMLDE, 2023)

Emergence of Direction Selectivity and Motion Strength in Dot Motion Task Through Deep Reinforcement Learning Networks. - Dolton Fernandes; Pramod S. Kaushik; Raju Surampudi Bapi (IJCNN, 2023)

Dynamic functional connectivity analysis in individuals with Autism Spectrum Disorder. - Pindi Krishna Chandra Prasad; Kamalaker Dadi; Bapi Raju Surampudi (IJCNN, 2023)

Application of Graph Theoretic measures for assessing efficacy of Stroke Rehabilitation. - Upadrasta Naga Sita Sravanthi; Kamalakar Dadi; Bapi Raju Surampudi; P. N. Sylaja; C. Kesavadas; Srijithesh PR; Rinta Paul (IJCNN, 2023)

Modelling Grid Navigation Using Reinforcement Learning Linear Ballistic Accumulators. - Gautham Venugopal; Bapi Surampudi Raju (IJCNN, 2023)

Speech Taskonomy: Which Speech Tasks are the most Predictive of fMRI Brain Activity? - Subba Reddy Oota; Veeral Agarwal; Mounika Marreddy; Manish Gupta 001; Raju S. Bapi (INTERSPEECH, 2023)

Exploring Emergent Properties of Recurrent Neural Networks Using a Novel Energy Function Formalism. - Rakesh Sengupta; Surampudi Bapi Raju; Anindya Pattanayak (LOD (1), 2023)

Encoded Deep Vectors for Eukaryotic Exon Prediction. - Praveen Kumar Vesapogu; Bapi Raju Surampudi (PReMI, 2023)

Syntactic Structure Processing in the Brain while Listening. - Subba Reddy Oota; Mounika Marreddy; Manish Gupta 001; Bapi Raju Surampudi (CoRR, 2023)

Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey). - Subba Reddy Oota; Manish Gupta 001; Raju S. Bapi; Gaël Jobard; Frédéric Alexandre; Xavier Hinaut (CoRR, 2023)

Data-efficient Deep Learning Approach for Single-Channel EEG-Based Sleep Stage Classification with Model Interpretability. - Shivam Kumar Sharma; Suvadeep Maiti; S. Mythirayee; Srijithesh Rajendran; S. Bapi Raju (CoRR, 2023)

Language Models and Brain Alignment: Brain Encoding and Decoding. - Subba Reddy Oota; Raju Surampudi Bapi (COMAD/CODS (December), 2024)

Enhancing Healthcare with EOG: A Novel Approach to Sleep Stage Classification. - Suvadeep Maiti; Shivam Kumar Sharma; Raju S. Bapi (ICASSP, 2024)

Multi Dimensional Deep Encoding for Categorical Feature Space. - Madhavi Alamuri; Surampudi Bapi Raju; Atul Negi (ICCPR, 2024)

HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable HyperEdges. - Mehul Arora; Chirag Shantilal Jain; Lalith Bharadwaj Baru; Kamalaker Dadi; Raju S. Bapi (IJCNN, 2024)

Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain). - Subba Reddy Oota; Akshett Rai Jindal; Ishani Mondal; Khushbu Pahwa; Satya Sai Srinath Namburi GNVV; Manish Shrivastava 001; Maneesh Kumar Singh 002; Bapi Raju Surampudi; Manish Gupta 001 (ICLR, 2025)

Multi-modal brain encoding models for multi-modal stimuli. - Subba Reddy Oota; Khushbu Pahwa; Mounika Marreddy; Maneesh Kumar Singh 002; Manish Gupta 001; Bapi Raju Surampudi (ICLR, 2025)

Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey). - Subba Reddy Oota; Zijiao Chen; Manish Gupta 001; Bapi Raju Surampudi; Gaël Jobard; Frédéric Alexandre; Xavier Hinaut (Trans. Mach. Learn. Res., 2025)

Momentum Boosted Episodic Memory for Improving Learning in Long-Tailed RL Environments. - Dolton Fernandes; Pramod S. Kaushik; Harsh Shukla; Bapi Raju Surampudi (CoRR, 2025)

Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain). - Subba Reddy Oota; Akshett Jindal; Ishani Mondal; Khushbu Pahwa; Satya Sai Srinath Namburi; Manish Shrivastava 001; Maneesh Kumar Singh 002; Raju Surampudi Bapi; Manish Gupta 001 (CoRR, 2025)

Instruction-Tuned Video-Audio Models Elucidate Functional Specialization in the Brain. - Subba Reddy Oota; Khushbu Pahwa; Prachi Jindal; Satya Sai Srinath Namburi; Maneesh Kumar Singh 002; Tanmoy Chakraborty 002; Raju S. Bapi; Manish Gupta 001 (CoRR, 2025)