Kumar, Abhishek

49 publications

ICLR 2025 RB-Modulation: Training-Free Stylization Using Reference-Based Modulation Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu

JMLR 2025 Score-Based Causal Representation Learning: Linear and General Transformations Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer

ICLRW 2025 Wanda++: Pruning Large Language Models via Regional Gradients Yifan Yang, Kai Zhen, Bhavana Ganesh, Aram Galstyan, Goeric Huybrechts, Markus Müller, Jonas M. Kübler, Rupak Vignesh Swaminathan, Athanasios Mouchtaris, Sravan Babu Bodapati, Nathan Susanj, Zheng Zhang, Jack FitzGerald, Abhishek Kumar

CVPR 2024 Beyond First-Order Tweedie: Solving Inverse Problems Using Latent Diffusion Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu

TMLR 2024 Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh, John D Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T Parisi, Abhishek Kumar, Alexander A Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura A Culp, Lechao Xiao, Maxwell Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel

CVPRW 2024 ControlPolypNet: Towards Controlled Colon Polyp Synthesis for Improved Polyp Segmentation Vanshali Sharma, Abhishek Kumar, Debesh Jha, Manas Kamal Bhuyan, Pradip K. Das, Ulas Bagci

TMLR 2024 Enhancing Contrastive Clustering with Negative Pair-Guided Regularization Abhishek Kumar, Anish Chakrabarty, Sankha Subhra Mullick, Swagatam Das

ICLR 2024 Small-Scale Proxies for Large-Scale Transformer Training Instabilities Mitchell Wortsman, Peter J Liu, Lechao Xiao, Katie E Everett, Alexander A Alemi, Ben Adlam, John D Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith

NeurIPS 2024 The Group Robustness Is in the Details: Revisiting Finetuning Under Spurious Correlations Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar

ICLR 2023 Distributionally Robust Post-Hoc Classifiers Under Prior Shifts Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

NeurIPSW 2023 Early Weight Averaging Meets High Learning Rates for LLM Pre-Training Sunny Sanyal, Atula Tejaswi Neerkaje, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi

NeurIPS 2023 Towards Last-Layer Retraining for Group Robustness with Fewer Annotations Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar

AAAI 2023 UEQMS: UMAP Embedded Quick Mean Shift Algorithm for High Dimensional Clustering Abhishek Kumar, Swagatam Das, Rammohan Mallipeddi

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

NeurIPSW 2022 Dropout Disagreement: A Recipe for Group Robustness with Fewer Annotations Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar

NeurIPSW 2022 Fast Implicit Constrained Optimization of Non-Decomposable Objectives for Deep Networks Yatong Chen, Abhishek Kumar, Yang Liu, Ehsan Amid

CVPR 2022 GridShift: A Faster Mode-Seeking Algorithm for Image Segmentation and Object Tracking Abhishek Kumar, Oladayo S. Ajani, Swagatam Das, Rammohan Mallipeddi

ECCV 2022 Master of All: Simultaneous Generalization of Urban-Scene Segmentation to All Adverse Weather Conditions Nikhil Reddy, Abhinav Singhal, Abhishek Kumar, Mahsa Baktashmotlagh, Chetan Arora

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

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

ICML 2021 Implicit Rate-Constrained Optimization of Non-Decomposable Objectives Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter

ICCV 2021 Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval Min Jin Chong, Wen-Sheng Chu, Abhishek Kumar, David Forsyth

MLHC 2021 Risk Score Learning for COVID-19 Contact Tracing Apps Kevin Murphy, Abhishek Kumar, Stylianos Serghiou

ICLR 2021 Score-Based Generative Modeling Through Stochastic Differential Equations Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole

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

ICML 2020 On Implicit Regularization in $β$-VAEs Abhishek Kumar, Ben Poole

AISTATS 2020 Regularized Autoencoders via Relaxed Injective Probability Flow Abhishek Kumar, Ben Poole, Kevin Murphy

ICLR 2020 Weakly Supervised Disentanglement with Guarantees Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole

CVPRW 2019 On the Robustness of Human Pose Estimation Naman Jain, Sahil Shah, Abhishek Kumar, Arjun Jain

NeurIPS 2018 Co-Regularized Alignment for Unsupervised Domain Adaptation Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogerio Feris, Bill Freeman, Gregory Wornell

NeurIPS 2018 Delta-Encoder: An Effective Sample Synthesis Method for Few-Shot Object Recognition Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogerio Feris, Raja Giryes, Alex Bronstein

CVPRW 2018 The Riemannian Geometry of Deep Generative Models Hang Shao, Abhishek Kumar, P. Thomas Fletcher

ICLR 2018 Variational Inference of Disentangled Latent Concepts from Unlabeled Observations Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan

CVPR 2017 Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification Yongxi Lu, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, Rogerio Feris

AISTATS 2017 Local Group Invariant Representations via Orbit Embeddings Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf

CVPR 2017 S3Pool: Pooling with Stochastic Spatial Sampling Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogerio Feris

NeurIPS 2017 Semi-Supervised Learning with GANs: Manifold Invariance with Improved Inference Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher

UAI 2016 Large-Scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen

AISTATS 2016 Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar

MLJ 2013 Beam Search Algorithms for Multilabel Learning Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan

ICML 2013 Fast Conical Hull Algorithms for Near-Separable Non-Negative Matrix Factorization Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur

ICML 2012 A Binary Classification Framework for Two-Stage Multiple Kernel Learning Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu, Hal Daumé Iii

CVPR 2012 Generalized Multiview Analysis: A Discriminative Latent Space Abhishek Sharma, Abhishek Kumar, Hal Daumé Iii, David W. Jacobs

ICML 2012 Learning Task Grouping and Overlap in Multi-Task Learning Abhishek Kumar, Hal Daumé Iii

ECML-PKDD 2012 Learning and Inference in Probabilistic Classifier Chains with Beam Search Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan

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

ICML 2011 A Co-Training Approach for Multi-View Spectral Clustering Abhishek Kumar, Hal Daumé Iii

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

NeurIPS 2010 Co-Regularization Based Semi-Supervised Domain Adaptation Abhishek Kumar, Avishek Saha, Hal Daume