Piyush Rai

44 papers · 2008–2023 · 10 conferences · across top CS/AI conferences

Achievements

+12 more ↓

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (19) 🌍 Conference Polyglot (10)

🗺️ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) 🤝 Dynamic Duo (12) 🏆 Keyword Champion 💎 Century Club (44) 🗃️ Keyword Collector (60) 🔥 Unstoppable (10) 📈 Trend Setter 🚀 Conference Pioneer ⚡ Prolific Year (10)

Conferences

NIPS (8) AAAI (7) AISTATS (7) CVPR (5) ICML (5) WACV (5) IJCAI (4) ACL (1) ACML (1) ECCV (1)

Top co-authors

Vinay Kumar Verma (12) Lawrence Carin (9) Pravendra Singh (8) Changwei Hu (5) Hal Daume (5) Abhishek Kumar (4) Nikhil Mehta (4) Dhanajit Brahma (3) Vinay P. Namboodiri (3) Pratik Mazumder (3)

Keywords

gibbs sampling (6) continual learning (6) generative model (6) bayesian inference (6) catastrophic forgetting (5) model compression (5) variational autoencoder (5) latent variable (4) zero-shot learning (4) generative adversarial network (4) multi-label learning (4) link prediction (4) convolutional neural network (4) label embedding (3) representation learning (3) variational inference (3) bayesian nonparametrics (3) nonparametric bayesian (3) lifelong learning (3) parameter efficiency (3)

Papers

Federated Learning with Uncertainty via Distilled Predictive Distributions ACML 2023 A Probabilistic Framework for Lifelong Test-Time Adaptation CVPR 2023 Novel Class Discovery without Forgetting ECCV 2022 Efficient Feature Transformations for Discriminative and Generative Continual Learning CVPR 2021 Rectification-Based Knowledge Retention for Continual Learning CVPR 2021 CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks NIPS 2021 Towards Zero-Shot Learning With Fewer Seen Class Examples WACV 2021 Few-Shot Lifelong Learning AAAI 2021 Generalized Adversarially Learned Inference AAAI 2021 Knowledge Consolidation based Class Incremental Online Learning with Limited Data IJCAI 2021 Bayesian Structural Adaptation for Continual Learning ICML 2021 P-SIF: Document Embeddings Using Partition Averaging AAAI 2020 Deep Attentive Ranking Networks for Learning to Order Sentences AAAI 2020 Jointly Trained Image and Video Generation using Residual Vectors WACV 2020 Variational Autoencoders for Sparse and Overdispersed Discrete Data AISTATS 2020 Leveraging Filter Correlations for Deep Model Compression WACV 2020 Calibrating CNNs for Lifelong Learning NIPS 2020 A Generative Framework for Zero Shot Learning with Adversarial Domain Adaptation WACV 2020 A "Network Pruning Network'' Approach to Deep Model Compression WACV 2020 Graph Representation Learning via Ladder Gamma Variational Autoencoders AAAI 2020 Meta-Learning for Generalized Zero-Shot Learning AAAI 2020 Deep Topic Models for Multi-label Learning AISTATS 2019 Distributional Semantics Meets Multi-Label Learning AAAI 2019 Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks ACL 2019 HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs CVPR 2019 Stochastic Blockmodels meet Graph Neural Networks ICML 2019 Play and Prune: Adaptive Filter Pruning for Deep Model Compression IJCAI 2019 Generalized Zero-Shot Learning via Synthesized Examples CVPR 2018 Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences AISTATS 2018 Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels IJCAI 2018 Scalable Generative Models for Multi-label Learning with Missing Labels ICML 2017 Deep Generative Models for Relational Data with Side Information ICML 2017 Topic-Based Embeddings for Learning from Large Knowledge Graphs AISTATS 2016 Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information AISTATS 2016 Scalable Probabilistic Tensor Factorization for Binary and Count Data IJCAI 2015 Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings NIPS 2015 Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors ICML 2014 Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression NIPS 2012 Online Learning of Multiple Tasks and Their Relationships AISTATS 2011 Message-Passing for Approximate MAP Inference with Latent Variables NIPS 2011 Co-regularized Multi-view Spectral Clustering NIPS 2011 Infinite Predictor Subspace Models for Multitask Learning AISTATS 2010 Multi-Label Prediction via Sparse Infinite CCA NIPS 2009 The Infinite Hierarchical Factor Regression Model NIPS 2008