Reconstruction-free inference on compressive measurements. - Suhas Lohit; Kuldeep Kulkarni; Pavan K. Turaga; Jian Wang 100; Aswin C. Sankaranarayanan (CVPR Workshops, 2015)

ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements. - Kuldeep Kulkarni; Suhas Lohit; Pavan K. Turaga; Ronan Kerviche; Amit Ashok (CVPR, 2016)

A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer. - Qiao Wang; Suhas Lohit; Meynard John Toledo; Matthew P. Buman; Pavan K. Turaga (EMBC, 2016)

Direct inference on compressive measurements using convolutional neural networks. - Suhas Lohit; Kuldeep Kulkarni; Pavan K. Turaga (ICIP, 2016)

ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements. - Kuldeep Kulkarni; Suhas Lohit; Pavan K. Turaga; Ronan Kerviche; Amit Ashok (CoRR, 2016)

Learning Invariant Riemannian Geometric Representations Using Deep Nets. - Suhas Lohit; Pavan K. Turaga (ICCV Workshops, 2017)

Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images. - Suhas Lohit; Kuldeep Kulkarni; Ronan Kerviche; Pavan K. Turaga; Amit Ashok (CoRR, 2017)

Predicting Dynamical Evolution of Human Activities From a Single Image. - Suhas Lohit; Ankan Bansal; Nitesh Shroff; Jaishanker K. Pillai; Pavan K. Turaga; Rama Chellappa (CVPR Workshops, 2018)

CS-VQA: Visual Question Answering with Compressively Sensed Images. - Li-Chi Huang; Kuldeep Kulkarni; Anik Jha; Suhas Lohit; Suren Jayasuriya; Pavan K. Turaga (ICIP, 2018)

Rate-Adaptive Neural Networks for Spatial Multiplexers. - Suhas Lohit; Rajhans Singh; Kuldeep Kulkarni; Pavan K. Turaga (CoRR, 2018)

Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images. - Suhas Lohit; Kuldeep Kulkarni; Ronan Kerviche; Pavan K. Turaga; Amit Ashok (IEEE Trans. Computational Imaging, 2018)

Rank-Regularized Measurement Operators for Compressive Imaging. - Suhas Lohit; Rajhans Singh; Kuldeep Kulkarni; Pavan K. Turaga (ACSSC, 2019)

Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. - Suhas Lohit; Qiao Wang; Pavan K. Turaga (CVPR, 2019)

Unrolled Projected Gradient Descent for Multi-spectral Image Fusion. - Suhas Lohit; Dehong Liu; Hassan Mansour; Petros T. Boufounos (ICASSP, 2019)

Rate-Invariant Autoencoding of Time-Series. - Kaushik Koneripalli; Suhas Lohit; Rushil Anirudh; Pavan K. Turaga (ICASSP, 2020)

Knowledge Distillation Thrives on Data Augmentation. - Huan Wang 014; Suhas Lohit; Michael Jones 002; Yun Fu 001 (CoRR, 2020)

Multi-head Knowledge Distillation for Model Compression. - Huan Wang 014; Suhas Lohit; Michael Jones 002; Yun Fu 001 (CoRR, 2020)

Rotation-Invariant Autoencoders for Signals on Spheres. - Suhas Lohit; Shubhendu Trivedi (CoRR, 2020)

Turnip: Time-Series U-Net With Recurrence For NIR Imaging PPG. - Armand Comas; Tim K. Marks; Hassan Mansour; Suhas Lohit; Yechi Ma; Xiaoming Liu 002 (ICIP, 2021)

Generative Patch Priors for Practical Compressive Image Recovery. - Rushil Anirudh; Suhas Lohit; Pavan K. Turaga (WACV, 2021)

Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. - Suhas Lohit; Rushil Anirudh; Pavan K. Turaga (WACV, 2021)

Learning Equivariances and Partial Equivariances from Data. - David W. Romero; Suhas Lohit (CoRR, 2021)

Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. - Sk Miraj Ahmed; Suhas Lohit; Kuan-Chuan Peng; Michael Jones 002; Amit K. Roy-Chowdhury (ECCV (34), 2022)

Distributed Radar Autofocus Imaging Using Deep Priors. - Hassan Mansour; Suhas Lohit; Petros T. Boufounos (ICIP, 2022)

Learning Partial Equivariances From Data. - David W. Romero; Suhas Lohit (NeurIPS, 2022)

What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective. - Huan Wang 014; Suhas Lohit; Michael J. Jones 001; Yun Fu 001 (NeurIPS, 2022)

Model Compression Using Optimal Transport. - Suhas Lohit; Michael Jones 002 (WACV, 2022)

Are Deep Neural Networks SMARTer Than Second Graders? - Anoop Cherian; Kuan-Chuan Peng; Suhas Lohit; Kevin A. Smith 001; Joshua B. Tenenbaum (CVPR, 2023)

Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. - Eun Som Jeon; Suhas Lohit; Rushil Anirudh; Pavan K. Turaga (ICASSP, 2023)

Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. - Nithin Gopalakrishnan Nair; Anoop Cherian; Suhas Lohit; Ye Wang 001; Toshiaki Koike-Akino; Vishal M. Patel; Tim K. Marks (ICCV, 2023)

Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. - Manish Sharma; Moitreya Chatterjee; Kuan-Chuan Peng; Suhas Lohit; Michael J. Jones 001 (ICCV (Workshops), 2023)

Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent. - Vineet R. Shenoy; Tim K. Marks; Hassan Mansour; Suhas Lohit (ICIP, 2023)

Rotation-Equivariant Neural Networks for Cloud Removal from Satellite Images. - Suhas Lohit; Tim K. Marks (IEEECONF, 2024)

Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-Aware Spatio-Temporal Sampling. - Xinhang Liu; Yu-Wing Tai; Chi-Keung Tang; Pedro Miraldo; Suhas Lohit; Moitreya Chatterjee (CVPR, 2024)

TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. - Haomiao Ni; Bernhard Egger 001; Suhas Lohit; Anoop Cherian; Ye Wang 001; Toshiaki Koike-Akino; Sharon X. Huang; Tim K. Marks (CVPR, 2024)

Equivariant Spatio-temporal Self-supervision for LiDAR Object Detection. - Deepti Hegde; Suhas Lohit; Kuan-Chuan Peng; Michael J. Jones 001; Vishal M. Patel (ECCV (26), 2024)

Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. - Anoop Cherian; Kuan-Chuan Peng; Suhas Lohit; Joanna Matthiesen; Kevin A. Smith 001; Josh Tenenbaum 001 (NeurIPS, 2024)

Pixel-Grounded Prototypical Part Networks. - Zachariah Carmichael; Suhas Lohit; Anoop Cherian; Michael J. Jones 001; Walter J. Scheirer (WACV, 2024)

G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups. - Sourya Basu; Suhas Lohit; Matthew Brand (CoRR, 2024)

Multimodal 3D Object Detection on Unseen Domains. - Deepti Hegde; Suhas Lohit; Kuan-Chuan Peng; Michael Jones 002; Vishal Patel 001 (CVPR Workshops, 2025)

FreBIS: Frequency-Based Stratification for Neural Implicit Surface Representations. - Naoko Sawada; Pedro Miraldo; Suhas Lohit; Tim K. Marks; Moitreya Chatterjee (CVPR Workshops, 2025)

G-RepsNet: A Lightweight Construction of Equivariant Networks for Arbitrary Matrix Groups. - Sourya Basu; Suhas Lohit; Matthew Brand (Trans. Mach. Learn. Res., 2025)

Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models. - Vineet R. Shenoy; Suhas Lohit; Hassan Mansour; Rama Chellappa; Tim K. Marks (CoRR, 2025)

Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography. - Vineet R. Shenoy; Shaoju Wu; Armand Comas; Tim K. Marks; Suhas Lohit; Hassan Mansour (CoRR, 2025)

Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal. - Yuyang Hu; Suhas Lohit; Ulugbek S. Kamilov; Tim K. Marks (CoRR, 2025)

Programmatic Video Prediction Using Large Language Models. - Hao Tang; Kevin Ellis; Suhas Lohit; Michael J. Jones 001; Moitreya Chatterjee (CoRR, 2025)