| 2024 | BMVC | RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance. | Avideep Mukherjee, Soumya Banerjee, Piyush Rai, Vinay P. Namboodiri |
| 2024 | ICRA | VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference. | Soumya Banerjee, Vinay Kumar Verma, Avideep Mukherjee, Deepak Gupta, Vinay P. Namboodiri, Piyush Rai |
| 2023 | ACML | Federated Learning with Uncertainty via Distilled Predictive Distributions. | Shrey Bhatt, Aishwarya Gupta, Piyush Rai |
| 2023 | COMAD | Gradient Perturbation-based Efficient Deep Ensembles. | Amit Chandak, Purushottam Kar, Piyush Rai |
| 2023 | CVPR | A Probabilistic Framework for Lifelong Test-Time Adaptation. | Dhanajit Brahma, Piyush Rai |
| 2022 | CVPR | Spacing Loss for Discovering Novel Categories. | K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian |
| 2022 | ECCV | Novel Class Discovery Without Forgetting. | K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian |
| 2021 | AAAI | Generalized Adversarially Learned Inference. | Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai |
| 2021 | AAAI | Few-Shot Lifelong Learning. | Pratik Mazumder, Pravendra Singh, Piyush Rai |
| 2021 | ACII | Fine-Grained Emotion Prediction by Modeling Emotion Definitions. | Gargi Singh, Dhanajit Brahma, Piyush Rai, Ashutosh Modi |
| 2021 | CVPR | Rectification-Based Knowledge Retention for Continual Learning. | Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri |
| 2021 | CVPR | Efficient Feature Transformations for Discriminative and Generative Continual Learning. | Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin |
| 2021 | ICML | Bayesian Structural Adaptation for Continual Learning. | Abhishek Kumar, Sunabha Chatterjee, Piyush Rai |
| 2021 | IJCAI | Knowledge Consolidation based Class Incremental Online Learning with Limited Data. | Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai |
| 2021 | WACV | Towards Zero-Shot Learning with Fewer Seen Class Examples. | Vinay Kumar Verma, Ashish Mishra, Anubha Pandey, Hema A. Murthy, Piyush Rai |
| 2020 | AAAI | P-SIF: Document Embeddings Using Partition Averaging. | Vivek Gupta, Ankit Saw, Pegah Nokhiz, Praneeth Netrapalli, Piyush Rai, Partha P. Talukdar |
| 2020 | AAAI | Deep Attentive Ranking Networks for Learning to Order Sentences. | Pawan Kumar, Dhanajit Brahma, Harish Karnick, Piyush Rai |
| 2020 | AAAI | Graph Representation Learning via Ladder Gamma Variational Autoencoders. | Arindam Sarkar, Nikhil Mehta, Piyush Rai |
| 2020 | AAAI | Meta-Learning for Generalized Zero-Shot Learning. | Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai |
| 2020 | AISTATS | Variational Autoencoders for Sparse and Overdispersed Discrete Data. | He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou |
| 2020 | WACV | Jointly Trained Image and Video Generation using Residual Vectors. | Yatin Dandi, Aniket Das, Soumye Singhal, Vinay P. Namboodiri, Piyush Rai |
| 2020 | WACV | A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. | Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai |
| 2020 | WACV | Leveraging Filter Correlations for Deep Model Compression. | Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri |
| 2020 | WACV | A "Network Pruning Network" Approach to Deep Model Compression. | Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai |
| 2019 | AAAI | Distributional Semantics Meets Multi-Label Learning. | Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai |
| 2019 | ACL | Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks. | Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar |
| 2019 | AISTATS | Deep Topic Models for Multi-label Learning. | Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai |
| 2019 | CVPR | HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs. | Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri |
| 2019 | CVPR | Generative Model for Zero-Shot Sketch-Based Image Retrieval. | Vinay Kumar Verma, Aakansha Mishra, Ashish Mishra, Piyush Rai |
| 2019 | ICML | Stochastic Blockmodels meet Graph Neural Networks. | Nikhil Mehta, Lawrence Carin, Piyush Rai |
| 2019 | IJCAI | Play and Prune: Adaptive Filter Pruning for Deep Model Compression. | Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri |
| 2018 | AAAI | A Deep Generative Framework for Paraphrase Generation. | Ankush Gupta, Arvind Agarwal, Prawaan Singh, Piyush Rai |
| 2018 | AAAI | 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 |
| 2018 | AISTATS | Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. | He Zhao, Piyush Rai, Lan Du, Wray L. Buntine |
| 2018 | CVPR | Generalized Zero-Shot Learning via Synthesized Examples. | Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, Piyush Rai |
| 2018 | IJCAI | Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels. | Gundeep Arora, Anupreet Porwal, Kanupriya Agarwal, Avani Samdariya, Piyush Rai |
| 2018 | WACV | 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 |
| 2017 | AAAI | Non-Negative Inductive Matrix Completion for Discrete Dyadic Data. | Piyush Rai |
| 2017 | ICML | Deep Generative Models for Relational Data with Side Information. | Changwei Hu, Piyush Rai, Lawrence Carin |
| 2017 | ICML | Scalable Generative Models for Multi-label Learning with Missing Labels. | Vikas Jain, Nirbhay Modhe, Piyush Rai |
| 2017 | UAI | A Probabilistic Framework for Multi-Label Learning with Unseen Labels. | Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai |
| 2016 | AISTATS | Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. | Changwei Hu, Piyush Rai, Lawrence Carin |
| 2016 | AISTATS | Topic-Based Embeddings for Learning from Large Knowledge Graphs. | Changwei Hu, Piyush Rai, Lawrence Carin |
| 2016 | ASPLOS | Architecture-Adaptive Code Variant Tuning. | Saurav Muralidharan, Amit Roy, Mary W. Hall, Michael Garland, Piyush Rai |
| 2015 | AAAI | Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data. | Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin |
| 2015 | AAAI | Leveraging Features and Networks for Probabilistic Tensor Decomposition. | Piyush Rai, Yingjian Wang, Lawrence Carin |
| 2015 | AAAI | Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision. | Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin |
| 2015 | IJCAI | Scalable Probabilistic Tensor Factorization for Binary and Count Data. | Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin |
| 2015 | UAI | Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. | Changwei Hu, Piyush Rai, Lawrence Carin |
| 2014 | ICML | Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. | Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin |
| 2013 | ICDM | Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. | Joyce Jiyoung Whang, Piyush Rai, Inderjit S. Dhillon |
| 2012 | ICML | Flexible Modeling of Latent Task Structures in Multitask Learning. | Alexandre Passos, Piyush Rai, Jacques Wainer, Hal Daum III |
| 2011 | ICML | Beam Search based MAP Estimates for the Indian Buffet Process. | Piyush Rai, Hal Daum III |
| 2011 | INFOCOM | Distinguishing locations across perimeters using wireless link measurements. | Junxing Zhang, Sneha Kumar Kasera, Neal Patwari, Piyush Rai |
| 2010 | CIKM | Exploiting tag and word correlations for improved webpage clustering. | Anusua Trivedi, Piyush Rai, Scott L. DuVall, Hal Daum III |
| 2009 | IJCAI | Streamed Learning: One-Pass SVMs. | Piyush Rai, Hal Daum III, Suresh Venkatasubramanian |