Vikas Singh
74 papers · 2007–2025 · 9 conferences · across top CS/AI conferences
Achievements
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(18)
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Conferences
CVPR (21)
ICCV (13)
NIPS (12)
ICML (11)
AAAI (6)
ECCV (4)
ICLR (3)
UAI (3)
JMLR (1)
Top co-authors
Research topics
Keywords
brain imaging
(8)
riemannian manifold
(5)
harmonic analysis
(4)
manifold-valued datum
(4)
domain adaptation
(4)
longitudinal analysis
(4)
deep neural network
(4)
efficient computing
(4)
hypothesis testing
(4)
statistical testing
(3)
wavelet transform
(3)
alzheimer disease
(3)
medical imaging
(3)
wavelet analysis
(3)
linear programming
(2)
monte carlo sampling
(2)
image segmentation
(2)
matrix completion
(2)
statistical inference
(2)
neural architecture search
(2)
Papers
SimpleTM: A Simple Baseline for Multivariate Time Series Forecasting
ICLR 2025
Understanding Multi-compositional learning in Vision and Language models via Category Theory
ECCV 2024
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
ICLR 2024
FrameQuant: Flexible Low-Bit Quantization for Transformers
ICML 2024
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
ICML 2024
Implicit Representations via Operator Learning
ICML 2024
Efficient Discrete Multi Marginal Optimal Transport Regularization
ICLR 2023
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens
NIPS 2023
LookupFFN: Making Transformers Compute-lite for CPU inference
ICML 2023
Controlled Differential Equations on Long Sequences via Non-standard Wavelets
ICML 2023
Deep Unlearning via Randomized Conditionally Independent Hessians
CVPR 2022
Multi Resolution Analysis (MRA) for Approximate Self-Attention
ICML 2022
Forward Operator Estimation in Generative Models with Kernel Transfer Operators
ICML 2022
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
CVPR 2022
Understanding Uncertainty Maps in Vision With Statistical Testing
CVPR 2022
On the Versatile Uses of Partial Distance Correlation in Deep Learning
ECCV 2022
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs
NIPS 2021
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
NIPS 2021
Learning Invariant Representations using Inverse Contrastive Loss
AAAI 2021
Physarum Powered Differentiable Linear Programming Layers and Applications
AAAI 2021
Flow-based Generative Models for Learning Manifold to Manifold Mappings
AAAI 2021
NystrΓΆmformer: A NystrΓΆm-based Algorithm for Approximating Self-Attention
AAAI 2021
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
ICML 2021
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks
UAI 2021
A variational approximation for analyzing the dynamics of panel data
UAI 2021
Neural TMDlayer: Modeling Instantaneous Flow of Features via SDE Generators
ICCV 2021
Connecting What To Say With Where To Look by Modeling Human Attention Traces
CVPR 2021
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
CVPR 2021
Simpler Certified Radius Maximization by Propagating Covariances
CVPR 2021
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
ECCV 2020
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains
AAAI 2020
Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations
CVPR 2020
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains
ICCV 2019
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging
ICCV 2019
Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data
ICCV 2019
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
ICCV 2019
Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation
CVPR 2019
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
ICCV 2019
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence
AAAI 2019
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging
UAI 2019
Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks
ICCV 2019
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
NIPS 2018
A Biresolution Spectral Framework for Product Quantization
CVPR 2018
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning
CVPR 2018
Efficient Relative Attribute Learning using Graph Neural Networks
ECCV 2018
Online Graph Completion: Multivariate Signal Recovery in Computer Vision
CVPR 2017
Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging
CVPR 2017
The Incremental Multiresolution Matrix Factorization Algorithm
CVPR 2017
Filter Flow Made Practical: Massively Parallel and Lock-Free
CVPR 2017
A Geometric Framework for Statistical Analysis of Trajectories With Distinct Temporal Spans
ICCV 2017
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
ICML 2017
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks
CVPR 2016
Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP)
CVPR 2016
Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease
NIPS 2016
Experimental Design on a Budget for Sparse Linear Models and Applications
ICML 2016
Manifold-valued Dirichlet Processes
ICML 2015
An NMF Perspective on Binary Hashing
ICCV 2015
A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer
ICCV 2015
On Statistical Analysis of Neuroimages With Imperfect Registration
ICCV 2015
Statistical Inference Models for Image Datasets With Systematic Variations
CVPR 2015
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization
CVPR 2015
SnFFT: A Julia Toolkit for Fourier Analysis of Functions over Permutations
JMLR 2015
Interpolation on the Manifold of K Component GMMs
ICCV 2015
Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images
CVPR 2014
Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision
NIPS 2014
Incorporating User Interaction and Topological Constraints within Contour Completion via Discrete Calculus
CVPR 2013
GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity
ICCV 2013
Solving the multi-way matching problem by permutation synchronization
NIPS 2013
Speeding up Permutation Testing in Neuroimaging
NIPS 2013
Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems
CVPR 2013
Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination
NIPS 2012
Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging
NIPS 2012
Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
NIPS 2010
Ensemble Clustering using Semidefinite Programming
NIPS 2007