The Infinite Hierarchical Factor Regression Model. - Piyush Rai; Hal Daumé III (NIPS, 2008)

Streamed Learning: One-Pass SVMs. - Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian (IJCAI, 2009)

Multi-Label Prediction via Sparse Infinite CCA. - Piyush Rai; Hal Daumé III (NIPS, 2009)

Exploiting tag and word correlations for improved webpage clustering. - Anusua Trivedi; Piyush Rai; Scott L. DuVall; Hal Daumé III (SMUC@CIKM, 2010)

Infinite Predictor Subspace Models for Multitask Learning. - Piyush Rai; Hal Daumé III (AISTATS, 2010)

Beam Search based MAP Estimates for the Indian Buffet Process. - Piyush Rai; Hal Daumé III (ICML, 2011)

Video Scene Segmentation with a Semantic Similarity. - Niraj Kumar 001; Piyush Rai; Chandrika Pulla; C. V. Jawahar (IICAI, 2011)

Distinguishing locations across perimeters using wireless link measurements. - Junxing Zhang; Sneha Kumar Kasera; Neal Patwari; Piyush Rai (INFOCOM, 2011)

Message-Passing for Approximate MAP Inference with Latent Variables. - Jiarong Jiang; Piyush Rai; Hal Daumé III (NIPS, 2011)

Co-regularized Multi-view Spectral Clustering. - Abhishek Kumar 001; Piyush Rai; Hal Daumé III (NIPS, 2011)

Active Supervised Domain Adaptation. - Avishek Saha; Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian; Scott L. DuVall (ECML/PKDD (3), 2011)

Online Learning of Multiple Tasks and Their Relationships. - Avishek Saha; Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian (AISTATS, 2011)

Flexible Modeling of Latent Task Structures in Multitask Learning. - Alexandre Passos; Piyush Rai; Jacques Wainer; Hal Daumé III (ICML, 2012)

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression. - Piyush Rai; Abhishek Kumar 001; Hal Daumé III (NIPS, 2012)

Leveraging Social Bookmarks from Partially Tagged Corpus for Improved Web Page Clustering. - Anusua Trivedi; Piyush Rai; Hal Daumé III; Scott L. DuVall (ACM Trans. Intell. Syst. Technol., 2012)

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. - Joyce Jiyoung Whang; Piyush Rai; Inderjit S. Dhillon (ICDM, 2013)

Learning Latent Structures Via Bayesian Nonparametrics: New Models and Efficient Interference. - Piyush Rai (2013)

Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. - Piyush Rai; Yingjian Wang 004; Shengbo Guo; Gary Chen; David B. Dunson; Lawrence Carin (ICML, 2014)

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

Leveraging Features and Networks for Probabilistic Tensor Decomposition. - Piyush Rai; Yingjian Wang 004; Lawrence Carin (AAAI, 2015)

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

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

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. - Piyush Rai; Changwei Hu; Ricardo Henao; Lawrence Carin (NIPS, 2015)

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data. - Changwei Hu; Piyush Rai; Changyou Chen; Matthew Harding; Lawrence Carin (ECML/PKDD (2), 2015)

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

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 (AISTATS, 2016)

Architecture-Adaptive Code Variant Tuning. - Saurav Muralidharan; Amit Roy; Mary W. Hall; Michael Garland; Piyush Rai (ASPLOS, 2016)

Deep Metric Learning with Data Summarization. - Wenlin Wang; Changyou Chen; Wenlin Chen; Piyush Rai; Lawrence Carin (ECML/PKDD (1), 2016)

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification. - Wenlin Wang; Changyou Chen; Wenqi Wang 001; Piyush Rai; Lawrence Carin (CoRR, 2016)

Non-Negative Inductive Matrix Completion for Discrete Dyadic Data. - Piyush Rai (AAAI, 2017)

Deep Generative Models for Relational Data with Side Information. - Changwei Hu; Piyush Rai; Lawrence Carin (ICML, 2017)

Scalable Generative Models for Multi-label Learning with Missing Labels. - Vikas Jain; Nirbhay Modhe; Piyush Rai (ICML, 2017)

A Simple Exponential Family Framework for Zero-Shot Learning. - Vinay Kumar Verma; Piyush Rai (ECML/PKDD (2), 2017)

A Probabilistic Framework for Multi-Label Learning with Unseen Labels. - Abhilash Gaure; Aishwarya Gupta 001; Vinay Kumar Verma; Piyush Rai (UAI, 2017)

Leveraging Distributional Semantics for Multi-Label Learning. - Rahul Wadbude; Vivek Gupta 001; Piyush Rai; Nagarajan Natarajan; Harish Karnick (CoRR, 2017)

A Deep Generative Framework for Paraphrase Generation. - Ankush Gupta; Arvind Agarwal; Prawaan Singh; Piyush Rai (AAAI, 2018)

Zero-Shot Learning via Class-Conditioned Deep Generative Models. - Wenlin Wang; Yunchen Pu; Vinay Kumar Verma; Kai Fan 002; Yizhe Zhang 002; Changyou Chen; Piyush Rai; Lawrence Carin (AAAI, 2018)

Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. - He Zhao 001; Piyush Rai; Lan Du 002; Wray L. Buntine (AISTATS, 2018)

Generalized Zero-Shot Learning via Synthesized Examples. - Vinay Kumar Verma; Gundeep Arora; Ashish Mishra 001; Piyush Rai (CVPR, 2018)

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

A Generative Approach to Zero-Shot and Few-Shot Action Recognition. - Ashish Mishra 001; Vinay Kumar Verma; M. Shiva Krishna Reddy; Arulkumar Subramaniam; Piyush Rai; Anurag Mittal (WACV, 2018)

Graph Convolutional Networks based Word Embeddings. - Shikhar Vashishth; Prateek Yadav; Manik Bhandari; Piyush Rai; Chiranjib Bhattacharyya; Partha P. Talukdar (CoRR, 2018)

Distributional Semantics Meets Multi-Label Learning. - Vivek Gupta 001; Rahul Wadbude; Nagarajan Natarajan; Harish Karnick; Prateek Jain 002; Piyush Rai (AAAI, 2019)

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 (ACL (1), 2019)

Deep Topic Models for Multi-label Learning. - Rajat Panda; Ankit Pensia; Nikhil Mehta 002; Mingyuan Zhou; Piyush Rai (AISTATS, 2019)

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

Generative Model for Zero-Shot Sketch-Based Image Retrieval. - Vinay Kumar Verma; Aakansha Mishra; Ashish Mishra 001; Piyush Rai (CVPR Workshops, 2019)

Stochastic Blockmodels meet Graph Neural Networks. - Nikhil Mehta 002; Lawrence Carin; Piyush Rai (ICML, 2019)

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

Variational Autoencoders for Sparse and Overdispersed Discrete Data. - He Zhao 001; Piyush Rai; Lan Du 002; Wray L. Buntine; Mingyuan Zhou (CoRR, 2019)

A Meta-Learning Framework for Generalized Zero-Shot Learning. - Vinay Kumar Verma; Dhanajit Brahma; Piyush Rai (CoRR, 2019)

Refined α-Divergence Variational Inference via Rejection Sampling. - Rahul Sharma; Abhishek Kumar 001; Piyush Rai (CoRR, 2019)

Nonparametric Bayesian Structure Adaptation for Continual Learning. - Abhishek Kumar 001; Sunabha Chatterjee; Piyush Rai (CoRR, 2019)

On the relationship between multitask neural networks and multitask Gaussian Processes. - Karthikeyan K; Shubham Kumar Bharti; Piyush Rai (CoRR, 2019)

A flexible probabilistic framework for large-margin mixture of experts. - Archit Sharma; Siddhartha Saxena; Piyush Rai (Mach. Learn., 2019)

P-SIF: Document Embeddings Using Partition Averaging. - Vivek Gupta 001; Ankit Saw; Pegah Nokhiz; Praneeth Netrapalli; Piyush Rai; Partha P. Talukdar (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 002; Piyush Rai (AAAI, 2020)

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

Variational Autoencoders for Sparse and Overdispersed Discrete Data. - He Zhao 001; Piyush Rai; Lan Du 002; Wray L. Buntine; Dinh Phung 001; Mingyuan Zhou (AISTATS, 2020)

Calibrating CNNs for Lifelong Learning. - Pravendra Singh; Vinay Kumar Verma; Pratik Mazumder; Lawrence Carin; Piyush Rai (NeurIPS, 2020)

Jointly Trained Image and Video Generation using Residual Vectors. - Yatin Dandi; Aniket Das; Soumye Singhal; Vinay P. Namboodiri; 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 (WACV, 2020)

Leveraging Filter Correlations for Deep Model Compression. - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (WACV, 2020)

A "Network Pruning Network" Approach to Deep Model Compression. - Vinay Kumar Verma; Pravendra Singh; Vinay P. Namboodiri; Piyush Rai (WACV, 2020)

Quantile Regularization: Towards Implicit Calibration of Regression Models. - Saiteja Utpala; Piyush Rai (CoRR, 2020)

HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs. - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (Int. J. Comput. Vis., 2020)

Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning. - Pravendra Singh; Vinay Kumar Verma; Piyush Rai; Vinay P. Namboodiri (IEEE J. Sel. Top. Signal Process., 2020)

Generalized Adversarially Learned Inference. - Yatin Dandi; Homanga Bharadhwaj; Abhishek Kumar 001; Piyush Rai (AAAI, 2021)

Few-Shot Lifelong Learning. - Pratik Mazumder; Pravendra Singh; Piyush Rai (AAAI, 2021)

Fine-Grained Emotion Prediction by Modeling Emotion Definitions. - Gargi Singh; Dhanajit Brahma; Piyush Rai; Ashutosh Modi (ACII, 2021)

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

Efficient Feature Transformations for Discriminative and Generative Continual Learning. - Vinay Kumar Verma; Kevin J. Liang; Nikhil Mehta 002; Piyush Rai; Lawrence Carin (CVPR, 2021)

Bayesian Structural Adaptation for Continual Learning. - Abhishek Kumar 001; Sunabha Chatterjee; Piyush Rai (ICML, 2021)

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

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

Towards Zero-Shot Learning with Fewer Seen Class Examples. - Vinay Kumar Verma; Ashish Mishra 001; Anubha Pandey; Hema A. Murthy; Piyush Rai (WACV, 2021)

Efficient Continual Adaptation for Generative Adversarial Networks. - Sakshi Varshney; Vinay Kumar Verma; Lawrence Carin; Piyush Rai (CoRR, 2021)

Variational Rejection Particle Filtering. - Rahul Sharma; Soumya Banerjee; Dootika Vats; Piyush Rai (CoRR, 2021)

Hypernetworks for Continual Semi-Supervised Learning. - Dhanajit Brahma; Vinay Kumar Verma; Piyush Rai (CoRR, 2021)

NeurInt : Learning to Interpolate through Neural ODEs. - Avinandan Bose; Aniket Das; Yatin Dandi; Piyush Rai (CoRR, 2021)

SITA: Single Image Test-time Adaptation. - Ansh Khurana; Sujoy Paul; Piyush Rai; Soma Biswas; Gaurav Aggarwal (CoRR, 2021)

Spacing Loss for Discovering Novel Categories. - K. J. Joseph; Sujoy Paul; Gaurav Aggarwal; Soma Biswas; Piyush Rai; Kai Han 001; Vineeth N. Balasubramanian (CVPR Workshops, 2022)

Novel Class Discovery Without Forgetting. - K. J. Joseph; Sujoy Paul; Gaurav Aggarwal; Soma Biswas; Piyush Rai; Kai Han 001; Vineeth N. Balasubramanian (ECCV (24), 2022)

Semi-Supervised Super-Resolution. - Ankur Singh; Piyush Rai (CoRR, 2022)

Bayesian Federated Learning via Predictive Distribution Distillation. - Shrey Bhatt; Aishwarya Gupta; Piyush Rai (CoRR, 2022)

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents. - Kushagra Pandey; Avideep Mukherjee; Piyush Rai; Abhishek Kumar 001 (Trans. Mach. Learn. Res., 2022)

Federated Learning with Uncertainty via Distilled Predictive Distributions. - Shrey Bhatt; Aishwarya Gupta 001; Piyush Rai (ACML, 2023)

Gradient Perturbation-based Efficient Deep Ensembles. - Amit Chandak; Purushottam Kar; Piyush Rai (COMAD/CODS, 2023)

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

RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance. - Avideep Mukherjee; Soumya Banerjee; Piyush Rai; Vinay P. Namboodiri (BMVC, 2024)

VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference. - Soumya Banerjee; Vinay Kumar Verma; Avideep Mukherjee; Deepak Gupta; Vinay P. Namboodiri; Piyush Rai (ICRA, 2024)

Robust Black-box Testing of Deep Neural Networks using Co-Domain Coverage. - Aishwarya Gupta 001; Indranil Saha; Piyush Rai (CoRR, 2024)

Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization. - Shivam Pal; Aishwarya Gupta 001; Saqib Sarwar; Piyush Rai (CoRR, 2024)

Spatio-Temporal Forecasting of PM2.5 via Spatial-Diffusion guided Encoder-Decoder Architecture. - Malay Pandey; Vaishali Jain; Nimit Godhani; Sachchida Nand Tripathi; Piyush Rai (CoRR, 2024)

Text-Based Fine-Grained Emotion Prediction. - Gargi Singh; Dhanajit Brahma; Piyush Rai; Ashutosh Modi (IEEE Trans. Affect. Comput., 2024)

Rectification-Based Knowledge Retention for Task Incremental Learning. - Pratik Mazumder; Pravendra Singh; Piyush Rai; Vinay P. Namboodiri (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

NOVO: Unlearning-Compliant Vision Transformers. - Soumya Roy; Soumya Banerjee; Vinay Kumar Verma; Soumik Dasgupta; Deepak Gupta; Piyush Rai (CoRR, 2025)