← Authors

Piyush Rai

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

Achievements

πŸƒ Academic Marathon (15) 🌍 Conference Polyglot (10) 🌈 Renaissance Researcher (10) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (12) πŸ—ΊοΈ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) 🀝 Dynamic Duo (12) πŸ† Keyword Champion πŸ’Ž Century Club (44) πŸ—ƒοΈ Keyword Collector (60) πŸ”₯ Unstoppable (10) πŸ“ˆ Trend Setter πŸš€ 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