Hegde, Chinmay

56 publications

DMLR 2025 FlowBench: A Large Scale Benchmark for Flow Simulation over Complex Geometries Ronak Tali, Ali Rabeh, Cheng-Hau Yang, Mehdi Shadkhah, Samundra Karki, Abhisek Upadhyaya, Suriya Dhakshinamoorthy, Marjan Saadati, Soumik Sarkar, Adarsh Krishnamurthy, Chinmay Hegde, Aditya Balu, Baskar Ganapathysubramanian

ICLR 2025 Hidden in the Noise: Two-Stage Robust Watermarking for Images Kasra Arabi, Benjamin Feuer, R. Teal Witter, Chinmay Hegde, Niv Cohen

ICLRW 2025 Hidden in the Noise: Two-Stage Robust Watermarking for Images Kasra Arabi, Benjamin Feuer, R. Teal Witter, Chinmay Hegde, Niv Cohen

WACV 2025 Leveraging Vision Language Models for Specialized Agricultural Tasks Muhammad Arbab Arshad, Talukder Zaki Jubery, Tirtho Roy, Rim Nassiri, Asheesh K. Singh, Arti Singh, Chinmay Hegde, Baskar Ganapathysubramanian, Aditya Balu, Adarsh Krishnamurthy, Soumik Sarkar

ICLR 2025 LiveBench: A Challenging, Contamination-Limited LLM Benchmark Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha Venkat Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum

ICCV 2025 SEAL: Semantic Aware Image Watermarking Kasra Arabi, R. Teal Witter, Chinmay Hegde, Niv Cohen

NeurIPS 2025 VeriThoughts: Enabling Automated Verilog Code Generation Using Reasoning and Formal Verification Patrick Yubeaton, Andre Nakkab, Weihua Xiao, Luca Collini, Ramesh Karri, Chinmay Hegde, Siddharth Garg

NeurIPS 2025 When Are Concepts Erased from Diffusion Models? Kevin Lu, Nicky Kriplani, Rohit Gandikota, Minh Pham, David Bau, Chinmay Hegde, Niv Cohen

ICML 2025 WildChat-50m: A Deep Dive into the Role of Synthetic Data in Post-Training Benjamin Feuer, Chinmay Hegde

NeurIPSW 2024 A Unified Convergence Theory for Large Language Model Efficient Fine-Tuning Zhanhong Jiang, Nastaran Saadati, Aditya Balu, Minh Pham, Joshua Russell Waite, Nasla Saleem, Chinmay Hegde, Soumik Sarkar

COLT 2024 Agnostic Active Learning of Single Index Models with Linear Sample Complexity Aarshvi Gajjar, Wai Ming Tai, Xu Xingyu, Chinmay Hegde, Christopher Musco, Yi Li

NeurIPSW 2024 Assisted Few-Shot Learning for Vision-Language Models in Agricultural Stress Phenotype Identification Muhammad Arbab Arshad, Talukder Zaki Jubery, Asheesh K Singh, Arti Singh, Chinmay Hegde, Baskar Ganapathysubramanian, Aditya Balu, Adarsh Krishnamurthy, Soumik Sarkar

NeurIPS 2024 BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity Chih-Hsuan Yang, Ben Feuer, Zaki Jubery, Zi K. Deng, Andre Nakkab, Md Zahid Hasan, Shivani Chiranjeevi, Kelly Marshall, Nirmal Baishnab, Asheesh K Singh, Arti Singh, Soumik Sarkar, Nirav Merchant, Chinmay Hegde, Baskar Ganapathysubramanian

ICLR 2024 Circumventing Concept Erasure Methods for Text-to-Image Generative Models Minh Pham, Kelly O. Marshall, Niv Cohen, Govind Mittal, Chinmay Hegde

CVPR 2024 DIMAT: Decentralized Iterative Merging-and-Training for Deep Learning Models Nastaran Saadati, Minh Pham, Nasla Saleem, Joshua R. Waite, Aditya Balu, Zhanong Jiang, Chinmay Hegde, Soumik Sarkar

NeurIPSW 2024 Hidden in the Noise: Two-Stage Robust Watermarking for Images Kasra Arabi, Benjamin Feuer, R. Teal Witter, Chinmay Hegde, Niv Cohen

TMLR 2024 PriViT: Vision Transformers for Private Inference Naren Dhyani, Jianqiao Cambridge Mo, Patrick Yubeaton, Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde

CVPRW 2024 SDFConnect: Neural Implicit Surface Reconstruction of a Sparse Point Cloud with Topological Constraints Anushrut Jignasu, Aditya Balu, Soumik Sarkar, Chinmay Hegde, Baskar Ganapathysubramanian, Adarsh Krishnamurthy

NeurIPS 2024 SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification Benjamin Feuer, Jiawei Xu, Niv Cohen, Patrick Yubeaton, Govind Mittal, Chinmay Hegde

NeurIPS 2024 Slice-100k: A Multimodal Dataset for Extrusion-Based 3D Printing Anushrut Jignasu, Kelly O. Marshall, Ankush Kumar Mishra, Lucas Nerone Rillo, Baskar Ganapathysubramanian, Aditya Balu, Chinmay Hegde, Adarsh Krishnamurthy

NeurIPSW 2024 SolidMark: Evaluating Image Memorization in Generative Models Nicky Kriplani, Minh Pham, Gowthami Somepalli, Chinmay Hegde, Niv Cohen

NeurIPSW 2024 SolidMark: How to Evaluate Memorization in Image Generative Models Nicky Kriplani, Minh Pham, Malikka Rajshahi, Chinmay Hegde, Niv Cohen

NeurIPS 2024 TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova, Chinmay Hegde, Frank Hutter, Micah Goldblum, Niv Cohen, Colin White

AISTATS 2023 Active Learning for Single Neuron Models with Lipschitz Non-Linearities Aarshvi Gajjar, Christopher Musco, Chinmay Hegde

TMLR 2023 Distributionally Robust Classification on a Data Budget Benjamin Feuer, Ameya Joshi, Minh Pham, Chinmay Hegde

ICLR 2023 Implicit Regularization for Group Sparsity Jiangyuan Li, Thanh V Nguyen, Chinmay Hegde, Raymond K. W. Wong

NeurIPSW 2023 Improved Bounds for Agnostic Active Learning of Single Index Models Aarshvi Gajjar, Xingyu Xu, Christopher Musco, Chinmay Hegde

NeurIPSW 2023 On the Computational Complexity of Inverting Generative Models Feyza Duman Keles, Chinmay Hegde

ALT 2023 On the Computational Complexity of Self-Attention Feyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde

NeurIPSW 2023 Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks Benjamin Feuer, Niv Cohen, Chinmay Hegde

AAAI 2022 MDPGT: Momentum-Based Decentralized Policy Gradient Tracking Zhanhong Jiang, Xian Yeow Lee, Sin Yong Tan, Kai Liang Tan, Aditya Balu, Young M. Lee, Chinmay Hegde, Soumik Sarkar

NeurIPSW 2022 Provable Active Learning of Neural Networks for Parametric PDEs Aarshvi Gajjar, Chinmay Hegde, Christopher P Musco

ICML 2022 Selective Network Linearization for Efficient Private Inference Minsu Cho, Ameya Joshi, Brandon Reagen, Siddharth Garg, Chinmay Hegde

ICMLW 2021 Adversarially Robust Learning via Entropic Regularization Gauri Jagatap, Ameya Joshi, Animesh Basak Chowdhury, Siddharth Garg, Chinmay Hegde

ICML 2021 Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar

NeurIPS 2021 Differentiable Spline Approximations Minsu Cho, Aditya Balu, Ameya Joshi, Anjana Deva Prasad, Biswajit Khara, Soumik Sarkar, Baskar Ganapathysubramanian, Adarsh Krishnamurthy, Chinmay Hegde

NeurIPS 2021 Implicit Sparse Regularization: The Impact of Depth and Early Stopping Jiangyuan Li, Thanh Nguyen, Chinmay Hegde, Ka Wai Wong

NeurIPSW 2020 Differentiable Programming for Piecewise Polynomial Functions Minsu Cho, Ameya Joshi, Xian Yeow Lee, Aditya Balu, Adarsh Krishnamurthy, Baskar Ganapathysubramanian, Soumik Sarkar, Chinmay Hegde

AAAI 2020 InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models Ameya Joshi, Minsu Cho, Viraj Shah, Balaji Sesha Sarath Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

ICLRW 2020 Nano-Material Configuration Design with Deep Surrogate Langevin Dynamics Thanh V. Nguyen, Youssef Mroueh, Samuel Hoffman, Payel Das, Pierre Dognin, Giuseppe Romano, Chinmay Hegde

AAAI 2020 Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents Xian Yeow Lee, Sambit Ghadai, Kai Liang Tan, Chinmay Hegde, Soumik Sarkar

NeurIPS 2019 Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors Gauri Jagatap, Chinmay Hegde

CVPRW 2019 Attribute-Controlled Traffic Data Augmentation Using Conditional Generative Models Amitangshu Mukherjee, Ameya Joshi, Soumik Sarkar, Chinmay Hegde

AISTATS 2019 On the Dynamics of Gradient Descent for Autoencoders Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde

NeurIPSW 2019 Phase Retrieval Using Untrained Neural Network Priors Gauri Jagatap, Chinmay Hegde

JMLR 2019 Provably Accurate Double-Sparse Coding Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde

AAAI 2018 A Provable Approach for Double-Sparse Coding Thanh Van Nguyen, Raymond K. W. Wong, Chinmay Hegde

ICML 2018 On Learning Sparsely Used Dictionaries from Incomplete Samples Thanh Nguyen, Akshay Soni, Chinmay Hegde

AISTATS 2018 Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation Mohammadreza Soltani, Chinmay Hegde

NeurIPS 2017 Collaborative Deep Learning in Fixed Topology Networks Zhanhong Jiang, Aditya Balu, Chinmay Hegde, Soumik Sarkar

NeurIPS 2017 Fast, Sample-Efficient Algorithms for Structured Phase Retrieval Gauri Jagatap, Chinmay Hegde

IJCAI 2016 A Nearly-Linear Time Framework for Graph-Structured Sparsity Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

NeurIPS 2016 Fast Recovery from a Union of Subspaces Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

ICML 2015 A Nearly-Linear Time Framework for Graph-Structured Sparsity Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

NeurIPS 2008 Sparse Signal Recovery Using Markov Random Fields Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard Baraniuk

NeurIPS 2007 Random Projections for Manifold Learning Chinmay Hegde, Michael Wakin, Richard Baraniuk