| 2026 | COLT | Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget (extended abstract). | Michael O. Harding, Vikas Singh, Kirthevasan Kandasamy |
| 2025 | ICLR | SimpleTM: A Simple Baseline for Multivariate Time Series Forecasting. | Hui Chen, Viet Luong, Lopamudra Mukherjee, Vikas Singh |
| 2024 | ECCV | Understanding Multi-compositional Learning in Vision and Language Models via Category Theory. | Sotirios Panagiotis Chytas, Hyunwoo J. Kim, Vikas Singh |
| 2024 | ICLR | Pooling Image Datasets with Multiple Covariate Shift and Imbalance. | Sotirios Panagiotis Chytas, Vishnu Suresh Lokhande, Vikas Singh |
| 2024 | ICML | FrameQuant: Flexible Low-Bit Quantization for Transformers. | Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang, Vikas Singh |
| 2024 | ICML | Implicit Representations via Operator Learning. | Sourav Pal, Harshavardhan Adepu, Clinton J. Wang, Polina Golland, Vikas Singh |
| 2024 | ICML | IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers. | Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh |
| 2023 | CCGRID | Disease Prediction using Chest X-ray Images in Serverless Data pipeline Framework. | Vikas Singh, Neha Singh, Mainak Adhikari |
| 2023 | ICASSP | Robustness and Convergence of Mirror Descent for Blind Deconvolution. | Ronak Mehta, Sathya N. Ravi, Vikas Singh |
| 2023 | ICLR | Efficient Discrete Multi Marginal Optimal Transport Regularization. | Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh |
| 2023 | ICML | Controlled Differential Equations on Long Sequences via Non-standard Wavelets. | Sourav Pal, Zhanpeng Zeng, Sathya N. Ravi, Vikas Singh |
| 2023 | ICML | LookupFFN: Making Transformers Compute-lite for CPU inference. | Zhanpeng Zeng, Michael Davies, Pranav Pulijala, Karthikeyan Sankaralingam, Vikas Singh |
| 2022 | CVPR | Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. | Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh |
| 2022 | CVPR | Deep Unlearning via Randomized Conditionally Independent Hessians. | Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi |
| 2022 | CVPR | Understanding Uncertainty Maps in Vision with Statistical Testing. | Jurijs Nazarovs, Zhichun Huang, Songwong Tasneeyapant, Rudrasis Chakraborty, Vikas Singh |
| 2022 | ECCV | On the Versatile Uses of Partial Distance Correlation in Deep Learning. | Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty, Vikas Singh |
| 2022 | ICML | Forward Operator Estimation in Generative Models with Kernel Transfer Operators. | Zhichun Huang, Rudrasis Chakraborty, Vikas Singh |
| 2022 | ICML | Multi Resolution Analysis (MRA) for Approximate Self-Attention. | Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn Moo Fung, Vikas Singh |
| 2021 | AAAI | Learning Invariant Representations using Inverse Contrastive Loss. | Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh |
| 2021 | AAAI | Physarum Powered Differentiable Linear Programming Layers and Applications. | Zihang Meng, Sathya N. Ravi, Vikas Singh |
| 2021 | AAAI | Nystrmformer: A Nystrm-based Algorithm for Approximating Self-Attention. | Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh |
| 2021 | AAAI | Flow-based Generative Models for Learning Manifold to Manifold Mappings. | Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh |
| 2021 | CVPR | Connecting What To Say With Where To Look by Modeling Human Attention Traces. | Zihang Meng, Licheng Yu, Ning Zhang, Tamara L. Berg, Babak Damavandi, Vikas Singh, Amy Bearman |
| 2021 | CVPR | MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. | Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen |
| 2021 | CVPR | Simpler Certified Radius Maximization by Propagating Covariances. | Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh |
| 2021 | ICCV | Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators. | Zihang Meng, Vikas Singh, Sathya N. Ravi |
| 2021 | ICML | You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. | Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Moo Fung, Vikas Singh |
| 2021 | UAI | A variational approximation for analyzing the dynamics of panel data. | Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh |
| 2021 | UAI | Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks. | Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh |
| 2020 | AAAI | Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. | Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh |
| 2020 | CVPR | Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations. | Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh |
| 2020 | ECCV | FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. | Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh |
| 2019 | AAAI | Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. | Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh |
| 2019 | CVPR | Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation. | Yunyang Xiong, Hyunwoo J. Kim, Vikas Singh |
| 2019 | ICCV | Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data. | Rudrasis Chakraborty, Xingjian Zhen, Nicholas Vogt, Barbara B. Bendlin, Vikas Singh |
| 2019 | ICCV | Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging. | Seong Jae Hwang, Zirui Tao, Vikas Singh, Won Hwa Kim |
| 2019 | ICCV | Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains. | Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong |
| 2019 | ICCV | DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. | Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh |
| 2019 | ICCV | Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks. | Yiyou Sun, Sathya N. Ravi, Vikas Singh |
| 2019 | ICCV | Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? | Yunyang Xiong, Ronak Mehta, Vikas Singh |
| 2019 | UAI | Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging. | Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh |
| 2018 | CVPR | Tensorize, Factorize and Regularize: Robust Visual Relationship Learning. | Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh |
| 2018 | CVPR | A Biresolution Spectral Framework for Product Quantization. | Lopamudra Mukherjee, Sathya N. Ravi, Jiming Peng, Vikas Singh |
| 2018 | ECCV | Efficient Relative Attribute Learning Using Graph Neural Networks. | Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh |
| 2018 | MICCAI | A Natural Language Interface for Dissemination of Reproducible Biomedical Data Science. | Rogers Jeffrey Leo John, Jignesh M. Patel, Andrew L. Alexander, Vikas Singh, Nagesh Adluru |
| 2017 | CVPR | The Incremental Multiresolution Matrix Factorization Algorithm. | Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh |
| 2017 | CVPR | Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging. | Hyunwoo J. Kim, Nagesh Adluru, Heemanshu Suri, Baba C. Vemuri, Sterling C. Johnson, Vikas Singh |
| 2017 | CVPR | Online Graph Completion: Multivariate Signal Recovery in Computer Vision. | Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh |
| 2017 | CVPR | Filter Flow Made Practical: Massively Parallel and Lock-Free. | Sathya N. Ravi, Yunyang Xiong, Lopamudra Mukherjee, Vikas Singh |
| 2017 | CVPR | Riemannian Variance Filtering: An Independent Filtering Scheme for Statistical Tests on Manifold-Valued Data. | Ligang Zheng, Hyunwoo J. Kim, Nagesh Adluru, Michael A. Newton, Vikas Singh |
| 2017 | ICCV | A Geometric Framework for Statistical Analysis of Trajectories with Distinct Temporal Spans. | Rudrasis Chakraborty, Vikas Singh, Nagesh Adluru, Baba C. Vemuri |
| 2017 | ICML | When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications. | Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh |
| 2017 | MICCAI | Modeling Cognitive Trends in Preclinical Alzheimer's Disease (AD) via Distributions over Permutations. | Gregory Plumb, Lindsay Clark, Sterling C. Johnson, Vikas Singh |
| 2016 | CVPR | Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks. | Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh |
| 2016 | CVPR | Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP). | Won Hwa Kim, Hyunwoo J. Kim, Nagesh Adluru, Vikas Singh |
| 2016 | ECCV | Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging. | Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh |
| 2016 | ECCV | Abundant Inverse Regression Using Sufficient Reduction and Its Applications. | Hyunwoo J. Kim, Brandon M. Smith, Nagesh Adluru, Charles R. Dyer, Sterling C. Johnson, Vikas Singh |
| 2016 | ECCV | Network Flow Formulations for Learning Binary Hashing. | Lopamudra Mukherjee, Jiming Peng, Trevor Sigmund, Vikas Singh |
| 2016 | ICML | Experimental Design on a Budget for Sparse Linear Models and Applications. | Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh |
| 2015 | CVPR | Statistical inference models for image datasets with systematic variations. | Won Hwa Kim, Barbara B. Bendlin, Moo K. Chung, Sterling C. Johnson, Vikas Singh |
| 2015 | CVPR | Gaze-enabled egocentric video summarization via constrained submodular maximization. | Jia Xu, Lopamudra Mukherjee, Yin Li, Jamieson Warner, James M. Rehg, Vikas Singh |
| 2015 | ICCV | A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. | Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh |
| 2015 | ICCV | Interpolation on the Manifold of K Component GMMs. | Hyunwoo J. Kim, Nagesh Adluru, Monami Banerjee, Baba C. Vemuri, Vikas Singh |
| 2015 | ICCV | On Statistical Analysis of Neuroimages with Imperfect Registration. | Won Hwa Kim, Sathya N. Ravi, Sterling C. Johnson, Ozioma C. Okonkwo, Vikas Singh |
| 2015 | ICCV | An NMF Perspective on Binary Hashing. | Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh |
| 2015 | ICML | Manifold-valued Dirichlet Processes. | Hyunwoo J. Kim, Jia Xu, Baba C. Vemuri, Vikas Singh |
| 2014 | CVPR | Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images. | Hyunwoo J. Kim, Barbara B. Bendlin, Nagesh Adluru, Maxwell D. Collins, Moo K. Chung, Sterling C. Johnson, Richard J. Davidson, Vikas Singh |
| 2014 | ECCV | Spectral Clustering with a Convex Regularizer on Millions of Images. | Maxwell D. Collins, Ji Liu, Jia Xu, Lopamudra Mukherjee, Vikas Singh |
| 2014 | ECCV | Canonical Correlation Analysis on Riemannian Manifolds and Its Applications. | Hyunwoo J. Kim, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson, Baba C. Vemuri, Vikas Singh |
| 2014 | MICCAI | Randomized Denoising Autoencoders for Smaller and Efficient Imaging Based AD Clinical Trials. | Vamsi K. Ithapu, Vikas Singh, Ozioma C. Okonkwo, Sterling C. Johnson |
| 2013 | CVPR | Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems. | Won Hwa Kim, Moo K. Chung, Vikas Singh |
| 2013 | CVPR | Incorporating User Interaction and Topological Constraints within Contour Completion via Discrete Calculus. | Jia Xu, Maxwell D. Collins, Vikas Singh |
| 2013 | ICCV | GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity. | Jia Xu, Vamsi K. Ithapu, Lopamudra Mukherjee, James M. Rehg, Vikas Singh |
| 2013 | MICCAI | Multi-resolutional Brain Network Filtering and Analysis via Wavelets on Non-Euclidean Space. | Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Sylvia Charchut, Johnson J. GadElkarim, Lori L. Altshuler, Teena Moody, Anand R. Kumar, Vikas Singh, Alex D. Leow |
| 2012 | CVPR | Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions. | Maxwell D. Collins, Jia Xu, Leo J. Grady, Vikas Singh |
| 2012 | ECCV | Analyzing the Subspace Structure of Related Images: Concurrent Segmentation of Image Sets. | Lopamudra Mukherjee, Vikas Singh, Jia Xu, Maxwell D. Collins |
| 2012 | ICML | Incorporating Domain Knowledge in Matching Problems via Harmonic Analysis. | Deepti Pachauri, Maxwell D. Collins, Vikas Singh |
| 2011 | CVPR | Scale invariant cosegmentation for image groups. | Lopamudra Mukherjee, Vikas Singh, Jiming Peng |
| 2010 | ACCV | Network Connectivity via Inference over Curvature-Regularizing Line Graphs. | Maxwell D. Collins, Vikas Singh, Andrew L. Alexander |
| 2010 | CVPR | Learning kernels for variants of normalized cuts: Convex relaxations and applications. | Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chris Hinrichs |
| 2009 | CVPR | Half-integrality based algorithms for cosegmentation of images. | Lopamudra Mukherjee, Vikas Singh, Charles R. Dyer |
| 2009 | ICCV | An efficient algorithm for Co-segmentation. | Dorit S. Hochbaum, Vikas Singh |
| 2009 | ICCV | Label set perturbation for MRF based neuroimaging segmentation. | Dylan Hower, Vikas Singh, Sterling C. Johnson |
| 2009 | MICCAI | Topological Characterization of Signal in Brain Images Using Min-Max Diagrams. | Moo K. Chung, Vikas Singh, Peter T. Kim, Kim M. Dalton, Richard J. Davidson |
| 2009 | MICCAI | MKL for Robust Multi-modality AD Classification. | Chris Hinrichs, Vikas Singh, Guofan Xu, Sterling C. Johnson |
| 2008 | MICCAI | Cortical Surface Thickness as a Classifier: Boosting for Autism Classification. | Vikas Singh, Lopamudra Mukherjee, Moo K. Chung |
| 2007 | ICCV | Generalized Median Graphs: Theory and Applications. | Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Jinhui Xu, Michael J. Zeitz, Ronald Berezney |
| 2007 | ICCV | Limited view CT reconstruction via constrained metric labeling. | Vikas Singh, Petru M. Dinu, Lopamudra Mukherjee, Jinhui Xu, Kenneth R. Hoffmann |
| 2006 | MICCAI | On Mobility Analysis of Functional Sites from Time Lapse Microscopic Image Sequences of Living Cell Nucleus. | Lopamudra Mukherjee, Vikas Singh, Jinhui Xu, Kishore S. Malyavantham, Ronald Berezney |
| 2006 | SAC | Solving the brachytherapy seed localization problem using geometric and linear programming techniques. | Vikas Singh, Lopamudra Mukherjee, Jinhui Xu, Kenneth R. Hoffmann |
| 2004 | ISAAC | Efficient Job Scheduling Algorithms with Multi-type Contentions. | Zhenming Chen, Vikas Singh, Jinhui Xu |