Random Projections for Manifold Learning. - Chinmay Hegde; Michael B. Wakin; Richard G. Baraniuk (NIPS, 2007)

Sparse Signal Recovery Using Markov Random Fields. - Volkan Cevher; Marco F. Duarte; Chinmay Hegde; Richard G. Baraniuk (NIPS, 2008)

Compressive sensing of streams of pulses. - Chinmay Hegde; Richard G. Baraniuk (Allerton, 2009)

Recovery of compressible signals in unions of subspaces. - Marco F. Duarte; Chinmay Hegde; Volkan Cevher; Richard G. Baraniuk (CISS, 2009)

A Theoretical Analysis of Joint Manifolds - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (CoRR, 2009)

High Dimensional Data Fusion via Joint Manifold Learning. - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Compressive sensing of a superposition of pulses. - Chinmay Hegde; Richard G. Baraniuk (ICASSP, 2010)

Texas Hold 'Em algorithms for distributed compressive sensing. - Stephen R. Schnelle; Jason N. Laska; Chinmay Hegde; Marco F. Duarte; Mark A. Davenport; Richard G. Baraniuk (ICASSP, 2010)

Joint Manifolds for Data Fusion. - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (IEEE Trans. Image Process., 2010)

Model-based compressive sensing. - Richard G. Baraniuk; Volkan Cevher; Marco F. Duarte; Chinmay Hegde (IEEE Trans. Inf. Theory, 2010)

Go with the flow: Optical flow-based transport operators for image manifolds. - Aswin C. Sankaranarayanan; Chinmay Hegde; Sriram Nagaraj; Richard G. Baraniuk (Allerton, 2011)

Sampling and Recovery of Pulse Streams. - Chinmay Hegde; Richard G. Baraniuk (IEEE Trans. Signal Process., 2011)

SPIN: Iterative signal recovery on incoherent manifolds. - Chinmay Hegde; Richard G. Baraniuk (ISIT, 2012)

Near-isometric linear embeddings of manifolds. - Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk (SSP, 2012)

Multi-objective sensor-based replanning for a car-like robot. - Devin K. Grady; Mark Moll; Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk; Lydia E. Kavraki (SSRR, 2012)

Multi-robot target verification with reachability constraints. - Devin K. Grady; Mark Moll; Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk; Lydia E. Kavraki (SSRR, 2012)

Signal Recovery on Incoherent Manifolds. - Chinmay Hegde; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2012)

Nearly optimal linear embeddings into very low dimensions. - Elyot Grant; Chinmay Hegde; Piotr Indyk (GlobalSIP, 2013)

Nearly Linear-Time Model-Based Compressive Sensing. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (ICALP (1), 2014)

LIE operators for compressive sensing. - Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk (ICASSP, 2014)

Automatic fault localization using the generalized Earth Mover's distance. - Ludwig Schmidt; Chinmay Hegde; Piotr Indyk; Jonathan Kane; Ligang Lu; Detlef Hohl (ICASSP, 2014)

A fast approximation algorithm for tree-sparse recovery. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (ISIT, 2014)

Approximation-Tolerant Model-Based Compressive Sensing. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (SODA, 2014)

Seismic feature extraction using steiner tree methods. - Ludwig Schmidt; Chinmay Hegde; Piotr Indyk; Ligang Lu; Xingang Chi; Detlef Hohl (ICASSP, 2015)

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

Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. - Jayadev Acharya; Ilias Diakonikolas; Chinmay Hegde; Jerry Zheng Li; Ludwig Schmidt (PODS, 2015)

Efficient Upsampling of Natural Images. - Chinmay Hegde; Oncel Tuzel; Fatih Porikli (CoRR, 2015)

Fast Algorithms for Structured Sparsity. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (Bull. EATCS, 2015)

Approximation Algorithms for Model-Based Compressive Sensing. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (IEEE Trans. Inf. Theory, 2015)

NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings. - Chinmay Hegde; Aswin C. Sankaranarayanan; Wotao Yin; Richard G. Baraniuk (IEEE Trans. Signal Process., 2015)

Demixing sparse signals from nonlinear observations. - Mohammadreza Soltani; Chinmay Hegde (ACSSC, 2016)

A fast iterative algorithm for demixing sparse signals from nonlinear observations. - Mohammadreza Soltani; Chinmay Hegde (GlobalSIP, 2016)

Fast recovery from a union of subspaces. - Chinmay Hegde; Piotr Indyk; Ludwig Schmidt (NIPS, 2016)

A fast algorithm for demixing signals with structured sparsity. - Chinmay Hegde (SPCOM, 2016)

Bilevel feature selection in nearly-linear time. - Chinmay Hegde (SSP, 2016)

Reconstruction from periodic nonlinearities, with applications to HDR imaging. - Viraj Shah; Mohammadreza Soltani; Chinmay Hegde (ACSSC, 2017)

Parallel computing heuristics for low-rank matrix completion. - Charlie Hubbard; Chinmay Hegde (GlobalSIP, 2017)

Demixing structured superposition signals from periodic and aperiodic nonlinear observations. - Mohammadreza Soltani; Chinmay Hegde (GlobalSIP, 2017)

Stable recovery of sparse vectors from random sinusoidal feature maps. - Mohammadreza Soltani; Chinmay Hegde (ICASSP, 2017)

Fast, Sample-Efficient Algorithms for Structured Phase Retrieval. - Gauri Jagatap; Chinmay Hegde (NIPS, 2017)

Collaborative Deep Learning in Fixed Topology Networks. - Zhanhong Jiang; Aditya Balu; Chinmay Hegde; Soumik Sarkar (NIPS, 2017)

Phase Retrieval Using Structured Sparsity: A Sample Efficient Algorithmic Framework. - Gauri Jagatap; Chinmay Hegde (CoRR, 2017)

A Forward-Backward Approach for Visualizing Information Flow in Deep Networks. - Aditya Balu; Thanh Van Nguyen; Apurva Kokate; Chinmay Hegde; Soumik Sarkar (CoRR, 2017)

Fast Algorithms for Demixing Sparse Signals From Nonlinear Observations. - Mohammadreza Soltani; Chinmay Hegde (IEEE Trans. Signal Process., 2017)

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

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

Algorithmic Aspects of Inverse Problems Using Generative Models. - Chinmay Hegde (Allerton, 2018)

Phase Retrieval for Signals in Union of Subspaces. - M. Salman Asif; Chinmay Hegde (GlobalSIP, 2018)

Low Rank Fourier Ptychography. - Zhengyu Chen 003; Gauri Jagatap; Seyedehsara Nayer; Chinmay Hegde; Namrata Vaswani (ICASSP, 2018)

Sub-Diffraction Imaging Using Fourier Ptychography and Structured Sparsity. - Gauri Jagatap; Zhengyu Chen 003; Chinmay Hegde; Namrata Vaswani (ICASSP, 2018)

Solving Linear Inverse Problems Using Gan Priors: An Algorithm with Provable Guarantees. - Viraj Shah; Chinmay Hegde (ICASSP, 2018)

Model Corrected Low Rank Ptychography. - Gauri Jagatap; Zhengyu Chen 003; Chinmay Hegde; Namrata Vaswani (ICIP, 2018)

On Learning Sparsely Used Dictionaries from Incomplete Samples. - Thanh Van Nguyen; Akshay Soni; Chinmay Hegde (ICML, 2018)

Towards Sample-Optimal Methods for Solving Random Quadratic Equations with Structure. - Gauri Jagatap; Chinmay Hegde (ISIT, 2018)

Fast Low-Rank Matrix Estimation for Ill-Conditioned Matrices. - Mohammadreza Soltani; Chinmay Hegde (ISIT, 2018)

Freeway Traffic Incident Detection from Cameras: A Semi-Supervised Learning Approach. - Pranamesh Chakraborty; Anuj Sharma; Chinmay Hegde (ITSC, 2018)

Autoencoders Learn Generative Linear Models. - Thanh Van Nguyen; Raymond K. W. Wong; Chinmay Hegde (CoRR, 2018)

Learning ReLU Networks via Alternating Minimization. - Gauri Jagatap; Chinmay Hegde (CoRR, 2018)

Physics-aware Deep Generative Models for Creating Synthetic Microstructures. - Rahul Singh; Viraj Shah; Balaji Sesha Sarath Pokuri; Soumik Sarkar; Baskar Ganapathysubramanian; Chinmay Hegde (CoRR, 2018)

Fourier Phase Retrieval with Side Information Using Generative Prior. - Rakib Hyder; Chinmay Hegde; M. Salman Asif (ACSSC, 2019)

Leaming Structured Signals Using GAN s with Applications in Denoising and Demixing. - Mohammadreza Soltani; Swayambhoo Jain; Abhinav V. Sambasivan; Chinmay Hegde (ACSSC, 2019)

On the Dynamics of Gradient Descent for Autoencoders. - Thanh Van Nguyen; Raymond K. W. Wong; Chinmay Hegde (AISTATS, 2019)

Attribute-Controlled Traffic Data Augmentation Using Conditional Generative Models. - Amitangshu Mukherjee; Ameya Joshi; Soumik Sarkar; Chinmay Hegde (CVPR Workshops, 2019)

Signal Reconstruction From Modulo Observations. - Viraj Shah; Chinmay Hegde (GlobalSIP, 2019)

Reducing the Search Space for Hyperparameter Optimization Using Group Sparsity. - Minsu Cho; Chinmay Hegde (ICASSP, 2019)

Alternating Phase Projected Gradient Descent with Generative Priors for Solving Compressive Phase Retrieval. - Rakib Hyder; Viraj Shah; Chinmay Hegde; M. Salman Asif (ICASSP, 2019)

Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers. - Ameya Joshi; Amitangshu Mukherjee; Soumik Sarkar; Chinmay Hegde (ICCV, 2019)

Linearly Convergent Algorithms for Learning Shallow Residual Networks. - Gauri Jagatap; Chinmay Hegde (ISIT, 2019)

Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors. - Gauri Jagatap; Chinmay Hegde (NeurIPS, 2019)

A Kaczmarz Algorithm for Solving Tree Based Distributed Systems of Equations. - Chinmay Hegde; Fritz Keinert; Eric S. Weber (CoRR, 2019)

Encoding Invariances in Deep Generative Models. - Viraj Shah; Ameya Joshi; Sambuddha Ghosal; Balaji Sesha Sarath Pokuri; Soumik Sarkar; Baskar Ganapathysubramanian; Chinmay Hegde (CoRR, 2019)

One-Shot Neural Architecture Search via Compressive Sensing. - Minsu Cho; Mohammadreza Soltani; Chinmay Hegde (CoRR, 2019)

On Higher-order Moments in Adam. - Zhanhong Jiang; Aditya Balu; Sin Yong Tan; Young M. Lee; Chinmay Hegde; Soumik Sarkar (CoRR, 2019)

Provably Accurate Double-Sparse Coding. - Thanh Van Nguyen; Raymond K. W. Wong; Chinmay Hegde (J. Mach. Learn. Res., 2019)

Sample-Efficient Algorithms for Recovering Structured Signals From Magnitude-Only Measurements. - Gauri Jagatap; Chinmay Hegde (IEEE Trans. Inf. Theory, 2019)

Fast and Provable Algorithms for Learning Two-Layer Polynomial Neural Networks. - Mohammadreza Soltani; Chinmay Hegde (IEEE Trans. Signal Process., 2019)

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 (AAAI, 2020)

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

The Benefits of Side Information for Structured Phase Retrieval. - M. Salman Asif; Chinmay Hegde (EUSIPCO, 2020)

High Dynamic Range Imaging Using Deep Image Priors. - Gauri Jagatap; Chinmay Hegde (ICASSP, 2020)

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models. - Sergio Botelho; Ameya Joshi; Biswajit Khara; Vinay Rao; Soumik Sarkar; Chinmay Hegde; Santi Adavani; Baskar Ganapathysubramanian (MLHPC/AI4S@SC, 2020)

ESPN: Extremely Sparse Pruned Networks. - Minsu Cho; Ameya Joshi; Chinmay Hegde (CoRR, 2020)

Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery. - Minsu Cho; Mohammadreza Soltani; Chinmay Hegde (CoRR, 2020)

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models. - Sergio Botelho; Ameya Joshi; Biswajit Khara; Soumik Sarkar; Chinmay Hegde; Santi Adavani; Baskar Ganapathysubramanian (CoRR, 2020)

Adversarially Robust Learning via Entropic Regularization. - Gauri Jagatap; Animesh Basak Chowdhury; Siddharth Garg; Chinmay Hegde (CoRR, 2020)

Sample Efficient Fourier Ptychography for Structured Data. - Gauri Jagatap; Zhengyu Chen 003; Seyedehsara Nayer; Chinmay Hegde; Namrata Vaswani (IEEE Trans. Computational Imaging, 2020)

Decentralized Deep Learning Using Momentum-Accelerated Consensus. - Aditya Balu; Zhanhong Jiang; Sin Yong Tan; Chinmay Hegde; Young M. Lee; Soumik Sarkar (ICASSP, 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 (ICML, 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 Van Nguyen; Chinmay Hegde; Ka Wai Wong (NeurIPS, 2021)

Distributed multigrid neural solvers on megavoxel domains. - Aditya Balu; Sergio Botelho; Biswajit Khara; Vinay Rao; Soumik Sarkar; Chinmay Hegde; Adarsh Krishnamurthy; Santi Adavani; Baskar Ganapathysubramanian (SC, 2021)

Provably Convergent Algorithms for Solving Inverse Problems Using Generative Models. - Viraj Shah; Rakib Hyder; M. Salman Asif; Chinmay Hegde (CoRR, 2021)

Sphynx: ReLU-Efficient Network Design for Private Inference. - Minsu Cho; Zahra Ghodsi; Brandon Reagen; Siddharth Garg; Chinmay Hegde (CoRR, 2021)

Implicit Sparse Regularization: The Impact of Depth and Early Stopping. - Jiangyuan Li; Thanh Van Nguyen; Chinmay Hegde; Raymond K. W. Wong (CoRR, 2021)

Adversarial Token Attacks on Vision Transformers. - Ameya Joshi; Gauri Jagatap; Chinmay Hegde (CoRR, 2021)

Sparse signal recovery from modulo observations. - Viraj Shah; Chinmay Hegde (EURASIP J. Adv. Signal Process., 2021)

Adversarially Robust Learning via Entropic Regularization. - Gauri Jagatap; Ameya Joshi; Animesh Basak Chowdhury; Siddharth Garg; Chinmay Hegde (Frontiers Artif. Intell., 2021)

On Consensus-Optimality Trade-offs in Collaborative Deep Learning. - Zhanhong Jiang; Aditya Balu; Chinmay Hegde; Soumik Sarkar (Frontiers Artif. Intell., 2021)

Fast inverse design of microstructures via generative invariance networks. - Xian Yeow Lee; Joshua R. Waite; Chih-Hsuan Yang; Balaji Sesha Sarath Pokuri; Ameya Joshi; Aditya Balu; Chinmay Hegde; Baskar Ganapathysubramanian; Soumik Sarkar (Nat. Comput. Sci., 2021)

Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis. - Thanh Van Nguyen; Raymond K. W. Wong; Chinmay Hegde (IEEE Trans. Inf. Theory, 2021)

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 (AAAI, 2022)

Distributed Online Non-convex Optimization with Composite Regret. - Zhanhong Jiang; Aditya Balu; Xian Yeow Lee; Young M. Lee; Chinmay Hegde; Soumik Sarkar (Allerton, 2022)

Inverse Imaging with Generative Priors Via Langevin Dynamics. - Thanh Van Nguyen; Gauri Jagatap; Chinmay Hegde (ICASSP, 2022)

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

NURBS-Diff: A Differentiable Programming Module for NURBS. - Anjana Deva Prasad; Aditya Balu; Harshil Shah; Soumik Sarkar; Chinmay Hegde; Adarsh Krishnamurthy (Comput. Aided Des., 2022)

Smooth-Reduce: Leveraging Patches for Improved Certified Robustness. - Ameya Joshi; Minh Pham 005; Minsu Cho; Leonid Boytsov; Filipe Condessa; J. Zico Kolter; Chinmay Hegde (CoRR, 2022)

A Meta-Analysis of Distributionally-Robust Models. - Benjamin Feuer; Ameya Joshi; Chinmay Hegde (CoRR, 2022)

Revisiting Self-Distillation. - Minh Pham 005; Minsu Cho; Ameya Joshi; Chinmay Hegde (CoRR, 2022)

Gotcha: A Challenge-Response System for Real-Time Deepfake Detection. - Govind Mittal; Jiraphon Yenphraphai; Chinmay Hegde; Nasir D. Memon (CoRR, 2022)

Caption supervision enables robust learners. - Benjamin Feuer; Ameya Joshi; Chinmay Hegde (CoRR, 2022)

Neural PDE Solvers for Irregular Domains. - Biswajit Khara; Ethan Herron; Zhanhong Jiang; Aditya Balu; Chih-Hsuan Yang; Kumar Saurabh; Anushrut Jignasu; Soumik Sarkar; Chinmay Hegde; Adarsh Krishnamurthy; Baskar Ganapathysubramanian (CoRR, 2022)

Sphynx: A Deep Neural Network Design for Private Inference. - Minsu Cho; Zahra Ghodsi; Brandon Reagen; Siddharth Garg; Chinmay Hegde (IEEE Secur. Priv., 2022)

The Stochastic Augmented Lagrangian method for domain adaptation. - Zhanhong Jiang; Chao Liu 028; Young M. Lee; Chinmay Hegde; Soumik Sarkar; Dongxiang Jiang (Knowl. Based Syst., 2022)

Provable Compressed Sensing With Generative Priors via Langevin Dynamics. - Thanh Van Nguyen; Gauri Jagatap; Chinmay Hegde (IEEE Trans. Inf. Theory, 2022)

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

On The Computational Complexity of Self-Attention. - Feyza Duman Keles; Pruthuvi Mahesakya Wijewardena; Chinmay Hegde (ALT, 2023)

Identity-Preserving Aging of Face Images via Latent Diffusion Models. - Sudipta Banerjee; Govind Mittal; Ameya Joshi; Chinmay Hegde; Nasir D. Memon (IJCB, 2023)

Implicit Regularization for Group Sparsity. - Jiangyuan Li; Thanh Van Nguyen; Chinmay Hegde; Raymond K. W. Wong (ICLR, 2023)

Pathfinding Neural Cellular Automata. - Sam Earle; Ozlem Yildiz; Julian Togelius; Chinmay Hegde (CoRR, 2023)

LiT Tuned Models for Efficient Species Detection. - Andre Nakkab; Benjamin Feuer; Chinmay Hegde (CoRR, 2023)

ZeroForge: Feedforward Text-to-Shape Without 3D Supervision. - Kelly O. Marshall; Minh Pham 005; Ameya Joshi; Anushrut Jignasu; Aditya Balu; Adarsh Krishnamurthy; Chinmay Hegde (CoRR, 2023)

Circumventing Concept Erasure Methods For Text-to-Image Generative Models. - Minh Pham 005; Kelly O. Marshall; Chinmay Hegde (CoRR, 2023)

Towards Foundational AI Models for Additive Manufacturing: Language Models for G-Code Debugging, Manipulation, and Comprehension. - Anushrut Jignasu; Kelly O. Marshall; Baskar Ganapathysubramanian; Aditya Balu; Chinmay Hegde; Adarsh Krishnamurthy (CoRR, 2023)

On the Fine-Grained Hardness of Inverting Generative Models. - Feyza Duman Keles; Chinmay Hegde (CoRR, 2023)

PriViT: Vision Transformers for Fast Private Inference. - Naren Dhyani; Jianqiao Mo; Minsu Cho; Ameya Joshi; Siddharth Garg; Brandon Reagen; Chinmay Hegde (CoRR, 2023)

Exploring Dataset-Scale Indicators of Data Quality. - Benjamin Feuer; Chinmay Hegde (CoRR, 2023)

Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks. - Benjamin Feuer; Chinmay Hegde; Niv Cohen (CoRR, 2023)

Distributionally Robust Classification on a Data Budget. - Benjamin Feuer; Ameya Joshi; Minh Pham 005; Chinmay Hegde (Trans. Mach. Learn. Res., 2023)

Agnostic Active Learning of Single Index Models with Linear Sample Complexity. - Aarshvi Gajjar; Wai Ming Tai; Xingyu Xu 001; Chinmay Hegde; Christopher Musco; Yi Li (COLT, 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 (CVPR Workshops, 2024)

DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models. - Nastaran Saadati; Minh Pham 005; Nasla Saleem; Joshua R. Waite; Aditya Balu; Zhanhong Jiang; Chinmay Hegde; Soumik Sarkar (CVPR, 2024)

Gotcha: Real-Time Video Deepfake Detection via Challenge-Response. - Govind Mittal; Chinmay Hegde; Nasir D. Memon (EuroS&P, 2024)

Mitigating the Impact of Attribute Editing on Face Recognition. - Sudipta Banerjee; Sai Pranaswi Mullangi; Shruti Wagle; Chinmay Hegde; Nasir D. Memon (IJCB, 2024)

Circumventing Concept Erasure Methods For Text-To-Image Generative Models. - Minh Pham 005; Kelly O. Marshall; Niv Cohen; Govind Mittal; Chinmay Hegde (ICLR, 2024)

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

BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity. - Chih-Hsuan Yang; Benjamin Feuer; Talukder Zaki Jubery; Zi K. Deng; Andre Nakkab; Md. Zahid Hasan; Shivani Chiranjeevi; Kelly O. Marshall; Nirmal Baishnab; Asheesh Kumar Singh; Arti Singh; Soumik Sarkar; et al. (NeurIPS, 2024)

Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing. - Ashutosh Nirala; Ameya Joshi; Soumik Sarkar; Chinmay Hegde (SaTML, 2024)

Neural PDE Solvers for Irregular Domains. - Biswajit Khara; Ethan Herron; Aditya Balu; Dhruv Gamdha; Chih-Hsuan Yang; Kumar Saurabh; Anushrut Jignasu; Zhanhong Jiang; Soumik Sarkar; Chinmay Hegde; Baskar Ganapathysubramanian; Adarsh Krishnamurthy (Comput. Aided Des., 2024)

AI-assisted Tagging of Deepfake Audio Calls using Challenge-Response. - Govind Mittal; Arthur Jakobsson; Kelly O. Marshall; Chinmay Hegde; Nasir D. Memon (CoRR, 2024)

Robust Concept Erasure Using Task Vectors. - Minh Pham 005; Kelly O. Marshall; Chinmay Hegde; Niv Cohen (CoRR, 2024)

Arboretum: A Large Multimodal Dataset Enabling AI for Biodiversity. - Chih-Hsuan Yang; Benjamin Feuer; Zaki Jubery; Zi K. Deng; Andre Nakkab; Md. Zahid Hasan; Shivani Chiranjeevi; Kelly O. Marshall; Nirmal Baishnab; Asheesh K. Singh; Arti Singh; Soumik Sarkar; et al. (CoRR, 2024)

LiveBench: A Challenging, Contamination-Free LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Siddartha Naidu; Chinmay Hegde; Yann LeCun; et al. (CoRR, 2024)

AgEval: A Benchmark for Zero-Shot and Few-Shot Plant Stress Phenotyping with Multimodal LLMs. - 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 (CoRR, 2024)

Evaluation and Comparison of Visual Language Models for Transportation Engineering Problems. - Sanjita Prajapati; Tanu Singh; Chinmay Hegde; Pranamesh Chakraborty (CoRR, 2024)

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; et al. (CoRR, 2024)

TruncFormer: Private LLM Inference Using Only Truncations. - Patrick Yubeaton; Jianqiao Mo; Karthik Garimella; Nandan Kumar Jha; Brandon Reagen; Chinmay Hegde; Siddharth Garg (CoRR, 2024)

STITCH: Surface reconstrucTion using Implicit neural representations with Topology Constraints and persistent Homology. - Anushrut Jignasu; Ethan Herron; Zhanhong Jiang; Soumik Sarkar; Chinmay Hegde; Baskar Ganapathysubramanian; Aditya Balu; Adarsh Krishnamurthy (CoRR, 2024)

PriViT: Vision Transformers for Private Inference. - Naren Dhyani; Jianqiao Cambridge Mo; Patrick Yubeaton; Minsu Cho; Ameya Joshi; Siddharth Garg; Brandon Reagen; Chinmay Hegde (Trans. Mach. Learn. Res., 2024)

ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models. - Benjamin Feuer; Yurong Liu; Chinmay Hegde; Juliana Freire (Proc. VLDB Endow., 2024)

Vision-Language Models Can Identify Distracted Driver Behavior From Naturalistic Videos. - Md. Zahid Hasan; Jiajing Chen; Jiyang Wang; Mohammed Shaiqur Rahman; Ameya Joshi; Senem Velipasalar; Chinmay Hegde; Anuj Sharma; Soumik Sarkar (IEEE Trans. Intell. Transp. Syst., 2024)

NeuFENet: neural finite element solutions with theoretical bounds for parametric PDEs. - Biswajit Khara; Aditya Balu; Ameya Joshi; Soumik Sarkar; Chinmay Hegde; Adarsh Krishnamurthy; Baskar Ganapathysubramanian (Eng. Comput., 2024)

Identity-Aware Facial Age Editing Using Latent Diffusion. - Sudipta Banerjee; Govind Mittal; Ameya Joshi; Sai Pranaswi Mullangi; Chinmay Hegde; Nasir D. Memon (IEEE Trans. Biom. Behav. Identity Sci., 2024)

RLS3: RL-Based Synthetic Sample Selection to Enhance Spatial Reasoning in Vision-Language Models for Indoor Autonomous Perception. - Joshua R. Waite; Md. Zahid Hasan; Qisai Liu; Zhanhong Jiang; Chinmay Hegde; Soumik Sarkar (ICCPS, 2025)

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

LiveBench: A Challenging, Contamination-Limited LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Sreemanti Dey; Shubh-Agrawal; Sandeep Singh Sandha; et al. (ICLR, 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 (WACV, 2025)

WavePulse: Real-time Content Analytics of Radio Livestreams. - Govind Mittal; Sarthak Gupta; Shruti Wagle; Chirag Chopra; Anthony J. DeMattee; Nasir D. Memon; Mustaque Ahamad; Chinmay Hegde (WWW, 2025)

Geometry Matters: Benchmarking Scientific ML Approaches for Flow Prediction around Complex Geometries. - Ali Rabeh; Ethan Herron; Aditya Balu; Soumik Sarkar; Chinmay Hegde; Adarsh Krishnamurthy; Baskar Ganapathysubramanian (CoRR, 2025)

WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training. - Benjamin Feuer; Chinmay Hegde (CoRR, 2025)

Huff-LLM: End-to-End Lossless Compression for Efficient LLM Inference. - Patrick Yubeaton; Tareq Mahmoud; Shehab Naga; Pooria Taheri; Tianhua Xia; Arun George; Yasmein Khalil; Sai Qian Zhang; Siddharth Joshi 001; Chinmay Hegde; Siddharth Garg (CoRR, 2025)

SolidMark: Evaluating Image Memorization in Generative Models. - Nicky Kriplani; Minh Pham 005; Gowthami Somepalli; Chinmay Hegde; Niv Cohen (CoRR, 2025)

SEAL: Semantic Aware Image Watermarking. - Kasra Arabi; R. Teal Witter; Chinmay Hegde; Niv Cohen (CoRR, 2025)

Decorum: A Language-Based Approach For Style-Conditioned Synthesis of Indoor 3D Scenes. - Kelly O. Marshall; Omid Poursaeed; Sergiu Oprea; Amit Kumar; Anushrut Jignasu; Chinmay Hegde; Yilei Li; Rakesh Ranjan (CoRR, 2025)

FaceCloak: Learning to Protect Face Templates. - Sudipta Banerjee; Anubhav Jain 002; Chinmay Hegde; Nasir D. Memon (CoRR, 2025)

When Are Concepts Erased From Diffusion Models? - Kevin Lu; Nicky Kriplani; Rohit Gandikota; Minh Pham 005; David Bau; Chinmay Hegde; Niv Cohen (CoRR, 2025)

Towards Large Reasoning Models for Agriculture. - Hossein Zaremehrjerdi; Shreyan Ganguly; Ashlyn Rairdin; Elizabeth Tranel; Benjamin Feuer; Juan Ignacio Di Salvo; Srikanth Panthulugiri; Hernan Torres Pacin; Victoria Moser; Sarah Jones; Joscif Raigne; Yanben Shen; et al. (CoRR, 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 (CoRR, 2025)

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models. - Nastaran Saadati; Zhanhong Jiang; Joshua R. Waite; Shreyan Ganguly; Aditya Balu; Chinmay Hegde; Soumik Sarkar (CoRR, 2025)

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models. - Shivani Chiranjeevi; Hossein Zaremehrjerdi; Zi K. Deng; Talukder Z. Jubery; Ari Grele; Arti Singh; Asheesh Kumar Singh; Soumik Sarkar; Nirav C. Merchant; Harold F. Greeney; Baskar Ganapathysubramanian; Chinmay Hegde (CoRR, 2025)

OpenThoughts: Data Recipes for Reasoning Models. - Etash Kumar Guha; Ryan Marten; Sedrick Keh; Negin Raoof; Georgios Smyrnis; Hritik Bansal; Marianna Nezhurina; Jean Mercat; Trung Vu 002; Zayne Sprague; Ashima Suvarna; Benjamin Feuer; et al. (CoRR, 2025)

MARVIS: Modality Adaptive Reasoning over VISualizations. - Benjamin Feuer; Lennart Purucker; Oussama Elachqar; Chinmay Hegde (CoRR, 2025)

DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation. - Ekta Balkrishna Gavas; Chinmay Hegde; Nasir D. Memon; Sudipta Banerjee (CoRR, 2025)

Query Efficient Structured Matrix Learning. - Noah Amsel; Pratyush Avi; Tyler Chen; Feyza Duman Keles; Chinmay Hegde; Cameron Musco; Christopher Musco; David Persson (CoRR, 2025)