Super-Resolution of Face Images Using Kernel PCA-Based Prior. - Ayan Chakrabarti; A. N. Rajagopalan 001; Rama Chellappa (IEEE Trans. Multim., 2007)

Color constancy beyond bags of pixels. - Ayan Chakrabarti; Keigo Hirakawa; Todd E. Zickler (CVPR, 2008)

Effective separation of sparse and non-sparse image features for denoising. - Ayan Chakrabarti; Keigo Hirakawa (ICASSP, 2008)

An Empirical Camera Model for Internet Color Vision. - Ayan Chakrabarti; Daniel Scharstein; Todd E. Zickler (BMVC, 2009)

Analyzing spatially-varying blur. - Ayan Chakrabarti; Todd E. Zickler; William T. Freeman (CVPR, 2010)

Statistics of real-world hyperspectral images. - Ayan Chakrabarti; Todd E. Zickler (CVPR, 2011)

Learning object color models from multi-view constraints. - Trevor Owens; Kate Saenko; Ayan Chakrabarti; Ying Xiong; Todd E. Zickler; Trevor Darrell (CVPR, 2011)

Depth and Deblurring from a Spectrally-Varying Depth-of-Field. - Ayan Chakrabarti; Todd E. Zickler (ECCV (5), 2012)

Image Restoration with Signal-dependent Camera Noise - Ayan Chakrabarti; Todd E. Zickler (CoRR, 2012)

Color Constancy with Spatio-Spectral Statistics. - Ayan Chakrabarti; Keigo Hirakawa; Todd E. Zickler (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Rethinking color cameras. - Ayan Chakrabarti; William T. Freeman; Todd E. Zickler (ICCP, 2014)

Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images. - Ayan Chakrabarti; Ying Xiong; Baochen Sun; Trevor Darrell; Daniel Scharstein; Todd E. Zickler; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Low-level vision by consensus in a spatial hierarchy of regions. - Ayan Chakrabarti; Ying Xiong; Steven J. Gortler; Todd E. Zickler (CVPR, 2015)

Color Constancy by Learning to Predict Chromaticity from Luminance. - Ayan Chakrabarti (NIPS, 2015)

From Shading to Local Shape. - Ying Xiong; Ayan Chakrabarti; Ronen Basri; Steven J. Gortler; David W. Jacobs; Todd E. Zickler (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Single-Image RGB Photometric Stereo with Spatially-Varying Albedo. - Ayan Chakrabarti; Kalyan Sunkavalli (3DV, 2016)

A Neural Approach to Blind Motion Deblurring. - Ayan Chakrabarti (ECCV (3), 2016)

Learning Sensor Multiplexing Design through Back-propagation. - Ayan Chakrabarti (NIPS, 2016)

Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions. - Ayan Chakrabarti; Jingyu Shao; Greg Shakhnarovich (NIPS, 2016)

Examining the Impact of Blur on Recognition by Convolutional Networks. - Igor Vasiljevic; Ayan Chakrabarti; Gregory Shakhnarovich (CoRR, 2016)

Jointly optimizing placement and inference for beacon-based localization. - Charles B. Schaff; David Yunis; Ayan Chakrabarti; Matthew R. Walter (IROS, 2017)

Stabilizing GAN Training with Multiple Random Projections. - Behnam Neyshabur; Srinadh Bhojanapalli; Ayan Chakrabarti (CoRR, 2017)

Learning to Separate Multiple Illuminants in a Single Image. - Zhuo Hui; Ayan Chakrabarti; Kalyan Sunkavalli; Aswin C. Sankaranarayanan (CVPR, 2019)

NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support. - Weidong Cao 001; Xin He; Ayan Chakrabarti; Xuan Zhang 001 (DATE, 2019)

Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices. - Weidong Cao 001; Liu Ke 001; Ayan Chakrabarti; Xuan Zhang 001 (ICCAD, 2019)

Jointly Learning to Construct and Control Agents using Deep Reinforcement Learning. - Charles B. Schaff; David Yunis; Ayan Chakrabarti; Matthew R. Walter (ICRA, 2019)

Backprop with Approximate Activations for Memory-efficient Network Training. - Ayan Chakrabarti; Benjamin Moseley (NeurIPS, 2019)

Training Image Estimators without Image Ground Truth. - Zhihao Xia; Ayan Chakrabarti (NeurIPS, 2019)

Learning Privacy Preserving Encodings Through Adversarial Training. - Francesco Pittaluga; Sanjeev J. Koppal; Ayan Chakrabarti (WACV, 2019)

Towards a MEMS-based Adaptive LIDAR. - Francesco Pittaluga; Zaid Tasneem; Justin Folden; Brevin Tilmon; Ayan Chakrabarti; Sanjeev J. Koppal (3DV, 2020)

Protecting Geolocation Privacy of Photo Collections. - Jinghan Yang; Ayan Chakrabarti; Yevgeniy Vorobeychik (AAAI, 2020)

Basis Prediction Networks for Effective Burst Denoising With Large Kernels. - Zhihao Xia; Federico Perazzi; Michaël Gharbi; Kalyan Sunkavalli; Ayan Chakrabarti (CVPR, 2020)

Generating and Exploiting Probabilistic Monocular Depth Estimates. - Zhihao Xia; Patrick Sullivan; Ayan Chakrabarti (CVPR, 2020)

Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising. - Zhihao Xia; Ayan Chakrabarti (WACV, 2020)

Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures. - Kyle Yee; Ayan Chakrabarti (WACV, 2020)

A MEMS-based Foveating LIDAR to enable Real-time Adaptive Depth Sensing. - Francesco Pittaluga; Zaid Tasneem; Justin Folden; Brevin Tilmon; Ayan Chakrabarti; Sanjeev J. Koppal (CoRR, 2020)

Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image Compositing. - Jinghan Yang; Adith Boloor; Ayan Chakrabarti; Xuan Zhang 001; Yevgeniy Vorobeychik (CoRR, 2020)

Guest Editors' Introduction to the Special Section on Computational Photography. - Ayan Chakrabarti; Kalyan Sunkavalli; David A. Forsyth (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

NeuADC: Neural Network-Inspired Synthesizable Analog-to-Digital Conversion. - Weidong Cao 001; Xin He; Ayan Chakrabarti; Xuan Zhang 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments. - Zhihao Xia; Michaël Gharbi; Federico Perazzi; Kalyan Sunkavalli; Ayan Chakrabarti (CVPR, 2021)

Understanding Robustness of Transformers for Image Classification. - Srinadh Bhojanapalli; Ayan Chakrabarti; Daniel Glasner; Daliang Li; Thomas Unterthiner; Andreas Veit (ICCV, 2021)

Can Optical Trojans Assist Adversarial Perturbations? - Adith Boloor; Tong Wu 010; Patrick Naughton; Ayan Chakrabarti; Xuan Zhang 001; Yevgeniy Vorobeychik (ICCVW, 2021)

Real-Time Edge Classification: Optimal Offloading under Token Bucket Constraints. - Ayan Chakrabarti; Roch Guérin; Chenyang Lu 001; Jiangnan Liu (SEC, 2021)

Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation. - Srinadh Bhojanapalli; Ayan Chakrabarti; Himanshu Jain; Sanjiv Kumar; Michal Lukasik; Andreas Veit (CoRR, 2021)

Leveraging redundancy in attention with Reuse Transformers. - Srinadh Bhojanapalli; Ayan Chakrabarti; Andreas Veit; Michal Lukasik; Himanshu Jain; Frederick Liu; Yin-Wen Chang; Sanjiv Kumar (CoRR, 2021)

Evaluating Neural Network-Inspired Analog-to-Digital Conversion With Low-Precision RRAM. - Weidong Cao 001; Liu Ke 001; Ayan Chakrabarti; Xuan Zhang 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

HOGEye: Neural Approximation of HOG Feature Extraction in RRAM-Based 3D-Stacked Image Sensors. - Tianrui Ma; Weidong Cao 001; Fei Qiao; Ayan Chakrabarti; Xuan Zhang 001 (ISLPED, 2022)

Adversarial Robustness of Deep Sensor Fusion Models. - Shaojie Wang; Tong Wu 010; Ayan Chakrabarti; Yevgeniy Vorobeychik (WACV, 2022)

PROVES: Establishing Image Provenance using Semantic Signatures. - Mingyang Xie; Manav Kulshrestha; Shaojie Wang; Jinghan Yang; Ayan Chakrabarti; Ning Zhang 017; Yevgeniy Vorobeychik (WACV, 2022)

Adaptive Edge Offloading for Image Classification Under Rate Limit. - Jiaming Qiu; Ruiqi Wang; Ayan Chakrabarti; Roch Guérin; Chenyang Lu 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

LeCA: In-Sensor Learned Compressive Acquisition for Efficient Machine Vision on the Edge. - Tianrui Ma; Adith Jagadish Boloor; Xiangxing Yang; Weidong Cao 001; Patrick Williams; Nan Sun 001; Ayan Chakrabarti; Xuan Zhang 001 (ISCA, 2023)

Benchmarking Robustness to Adversarial Image Obfuscations. - Florian Stimberg; Ayan Chakrabarti; Chun-Ta Lu; Hussein Hazimeh 001; Otilia Stretcu; Wei Qiao; Yintao Liu; Merve Kaya; Cyrus Rashtchian; Ariel Fuxman; Mehmet Tek; Sven Gowal (NeurIPS, 2023)

Substance or Style: What Does Your Image Embedding Know? - Cyrus Rashtchian; Charles Herrmann; Chun-Sung Ferng; Ayan Chakrabarti; Dilip Krishnan; Deqing Sun; Da-Cheng Juan; Andrew Tomkins (CoRR, 2023)

SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models. - Sadeep Jayasumana; Daniel Glasner; Srikumar Ramalingam; Andreas Veit; Ayan Chakrabarti; Sanjiv Kumar (CoRR, 2023)

Tree Recovery by Dynamic Programming. - Gustavo Gratacós; Ayan Chakrabarti; Tao Ju 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. - Sadeep Jayasumana; Daniel Glasner; Srikumar Ramalingam; Andreas Veit; Ayan Chakrabarti; Sanjiv Kumar (CVPR, 2024)

Rethinking FID: Towards a Better Evaluation Metric for Image Generation. - Sadeep Jayasumana; Srikumar Ramalingam; Andreas Veit; Daniel Glasner; Ayan Chakrabarti; Sanjiv Kumar (CVPR, 2024)

SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection. - Ke Ye; Heinrich Jiang; Afshin Rostamizadeh; Ayan Chakrabarti; Giulia DeSalvo; Jean-François Kagy; Lazaros Karydas; Gui Citovsky; Sanjiv Kumar (CoRR, 2024)

A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. - Ankit Singh Rawat; Veeranjaneyulu Sadhanala; Afshin Rostamizadeh; Ayan Chakrabarti; Wittawat Jitkrittum; Vladimir Feinberg; Seungyeon Kim 001; Hrayr Harutyunyan; Nikunj Saunshi; Zachary Nado; Rakesh Shivanna; Sashank J. Reddi; et al. (CoRR, 2024)

LatentCRF: Continuous CRF for Efficient Latent Diffusion. - Kanchana Ranasinghe; Sadeep Jayasumana; Andreas Veit; Ayan Chakrabarti; Daniel Glasner; Michael S. Ryoo; Srikumar Ramalingam; Sanjiv Kumar (CoRR, 2024)

Analyzing Similarity Metrics for Data Selection for Language Model Pretraining. - Dylan Sam; Ayan Chakrabarti; Afshin Rostamizadeh; Srikumar Ramalingam; Gui Citovsky; Sanjiv Kumar (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)