Rai, Piyush

70 publications

TMLR 2026 Probing Layer-Wise Memorization and Generalization in Deep Neural Networks via Model Stitching Aishwarya Gupta, Indranil Saha, Piyush Rai

TMLR 2025 Federated Learning with Uncertainty and Personalization via Efficient Second-Order Optimization Shivam Pal, Aishwarya Gupta, Saqib Sarwar, Piyush Rai

NeurIPSW 2024 Simple and Scalable Federated Learning with Uncertainty via Improved Variational Online Newton Shivam Pal, Aishwarya Gupta, Saqib Sarwar, Piyush Rai

NeurIPSW 2024 Understanding Memorization Using Representation Similarity Analysis and Model Stitching Aishwarya Gupta, Indranil Saha, Piyush Rai

CVPR 2023 A Probabilistic Framework for Lifelong Test-Time Adaptation Dhanajit Brahma, Piyush Rai

ACML 2023 Federated Learning with Uncertainty via Distilled Predictive Distributions Shrey Bhatt, Aishwarya Gupta, Piyush Rai

TMLR 2022 DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar

ECCV 2022 Novel Class Discovery Without Forgetting K J Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N Balasubramanian

CVPRW 2022 Spacing Loss for Discovering Novel Categories K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian

ICML 2021 Bayesian Structural Adaptation for Continual Learning Abhishek Kumar, Sunabha Chatterjee, Piyush Rai

NeurIPS 2021 CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai

CVPR 2021 Efficient Feature Transformations for Discriminative and Generative Continual Learning Vinay Kumar Verma, Kevin J Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin

AAAI 2021 Few-Shot Lifelong Learning Pratik Mazumder, Pravendra Singh, Piyush Rai

AAAI 2021 Generalized Adversarially Learned Inference Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai

IJCAI 2021 Knowledge Consolidation Based Class Incremental Online Learning with Limited Data Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai

NeurIPSW 2021 NeurInt: Learning to Interpolate Through Neural ODEs Avinandan Bose, Aniket Das, Yatin Dandi, Piyush Rai

CVPR 2021 Rectification-Based Knowledge Retention for Continual Learning Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri

WACV 2021 Towards Zero-Shot Learning with Fewer Seen Class Examples Vinay Kumar Verma, Ashish Mishra, Anubha Pandey, Hema A. Murthy, Piyush Rai

NeurIPSW 2021 VAEs Meet Diffusion Models: Efficient and High-Fidelity Generation Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar

WACV 2020 A "Network Pruning Network'' Approach to Deep Model Compression Vinay Kumar Verma, Pravendra Singh, Vinay Namboodri, Piyush Rai

WACV 2020 A Generative Framework for Zero Shot Learning with Adversarial Domain Adaptation Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai

NeurIPS 2020 Calibrating CNNs for Lifelong Learning Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai

AAAI 2020 Deep Attentive Ranking Networks for Learning to Order Sentences Pawan Kumar, Dhanajit Brahma, Harish Karnick, Piyush Rai

AAAI 2020 Graph Representation Learning via Ladder Gamma Variational Autoencoders Arindam Sarkar, Nikhil Mehta, Piyush Rai

WACV 2020 Jointly Trained Image and Video Generation Using Residual Vectors Yatin Dandi, Aniket Das, Soumye Singhal, Vinay Namboodiri, Piyush Rai

WACV 2020 Leveraging Filter Correlations for Deep Model Compression Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay Namboodiri

AAAI 2020 Meta-Learning for Generalized Zero-Shot Learning Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai

AAAI 2020 P-SIF: Document Embeddings Using Partition Averaging Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar

NeurIPSW 2020 Temperature Scaling for Quantile Calibration Saiteja Utpala, Piyush Rai

AISTATS 2020 Variational Autoencoders for Sparse and Overdispersed Discrete Data He Zhao, Piyush Rai, Lan Du, Wray Buntine, Dinh Phung, Mingyuan Zhou

MLJ 2019 A Flexible Probabilistic Framework for Large-Margin Mixture of Experts Archit Sharma, Siddhartha Saxena, Piyush Rai

AISTATS 2019 Deep Topic Models for Multi-Label Learning Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai

AAAI 2019 Distributional Semantics Meets Multi-Label Learning Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai

CVPRW 2019 Generative Model for Zero-Shot Sketch-Based Image Retrieval Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai

CVPR 2019 HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

IJCAI 2019 Play and Prune: Adaptive Filter Pruning for Deep Model Compression Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri

ICML 2019 Stochastic Blockmodels Meet Graph Neural Networks Nikhil Mehta, Lawrence Carin Duke, Piyush Rai

AAAI 2018 A Deep Generative Framework for Paraphrase Generation Ankush Gupta, Arvind Agarwal, Prawaan Singh, Piyush Rai

WACV 2018 A Generative Approach to Zero-Shot and Few-Shot Action Recognition Ashish Mishra, Vinay Kumar Verma, M. Shiva Krishna Reddy, Arulkumar Subramaniam, Piyush Rai, Anurag Mittal

AISTATS 2018 Bayesian Multi-Label Learning with Sparse Features and Labels, and Label Co-Occurrences He Zhao, Piyush Rai, Lan Du, Wray L. Buntine

CVPR 2018 Generalized Zero-Shot Learning via Synthesized Examples Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, Piyush Rai

IJCAI 2018 Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal, Avani Samdariya, Piyush Rai

AAAI 2018 Zero-Shot Learning via Class-Conditioned Deep Generative Models Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin

UAI 2017 A Probabilistic Framework for Multi-Label Learning with Unseen Labels Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai

ECML-PKDD 2017 A Simple Exponential Family Framework for Zero-Shot Learning Vinay Kumar Verma, Piyush Rai

ICML 2017 Deep Generative Models for Relational Data with Side Information Changwei Hu, Piyush Rai, Lawrence Carin

AAAI 2017 Non-Negative Inductive Matrix Completion for Discrete Dyadic Data Piyush Rai

ICML 2017 Scalable Generative Models for Multi-Label Learning with Missing Labels Vikas Jain, Nirbhay Modhe, Piyush Rai

ECML-PKDD 2016 Deep Metric Learning with Data Summarization Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin

AISTATS 2016 Non-Negative Matrix Factorization for Discrete Data with Hierarchical Side-Information Changwei Hu, Piyush Rai, Lawrence Carin

AISTATS 2016 Topic-Based Embeddings for Learning from Large Knowledge Graphs Changwei Hu, Piyush Rai, Lawrence Carin

AAAI 2015 Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin

AAAI 2015 Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin

NeurIPS 2015 Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin

AAAI 2015 Leveraging Features and Networks for Probabilistic Tensor Decomposition Piyush Rai, Yingjian Wang, Lawrence Carin

ECML-PKDD 2015 Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin

IJCAI 2015 Scalable Probabilistic Tensor Factorization for Binary and Count Data Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin

UAI 2015 Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors Changwei Hu, Piyush Rai, Lawrence Carin

ICML 2014 Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson, Lawrence Carin

ICML 2012 Flexible Modeling of Latent Task Structures in Multitask Learning Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé Iii

NeurIPS 2012 Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression Piyush Rai, Abhishek Kumar, Hal Daume

ECML-PKDD 2011 Active Supervised Domain Adaptation Avishek Saha, Piyush Rai, Hal Daumé Iii, Suresh Venkatasubramanian, Scott L. DuVall

ICML 2011 Beam Search Based MAP Estimates for the Indian Buffet Process Piyush Rai, Hal Daumé Iii

NeurIPS 2011 Co-Regularized Multi-View Spectral Clustering Abhishek Kumar, Piyush Rai, Hal Daume

NeurIPS 2011 Message-Passing for Approximate MAP Inference with Latent Variables Jiarong Jiang, Piyush Rai, Hal Daume

AISTATS 2011 Online Learning of Multiple Tasks and Their Relationships Avishek Saha, Piyush Rai, Hal Daumé Iii, Suresh Venkatasubramanian

AISTATS 2010 Infinite Predictor Subspace Models for Multitask Learning Piyush Rai, Hal Daumé

NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA Piyush Rai, Hal Daume

IJCAI 2009 Streamed Learning: One-Pass SVMs Piyush Rai, Hal Daumé Iii, Suresh Venkatasubramanian

NeurIPS 2008 The Infinite Hierarchical Factor Regression Model Piyush Rai, Hal Daume