Singh Group @ University of Wisconsin Madison

LCODEC-deep-unlearning

Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"

dual-glow

[ICCV'19] DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer

Partial_Distance_Correlation

This is the official GitHub for paper: On the Versatile Uses of Partial Distance Correlation in Deep Learning, in ECCV 2022

mobiledet-pytorch

PyTorch Implementation of MobileDet (https://arxiv.org/abs/2004.14525v3) backbones.

RECNN

On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging

uncertainty_with_rf

Understanding Uncertainty Maps in Vision with Statistical Testing

DatasetPooling

mcrepar

Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks

RCNet

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?

crow

DCNN

This is the published codes for Dilated Convolutional Neural Networks (DCNN) for Sequential Manifold-valued Data in Neuroimaging ICCV 2019

DeepHermites

Dual_Manifold_GLOW

This is the official webpage of the Flow-based Generative Models for Learning Manifold to Manifold Mappings in AAAI 2021

dynamic-k-activation

Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks

f1-opt

FairALM

GLapGAN

ic-loss

PyTorch and Tensorflow implementation of inverse contrastive loss - https://arxiv.org/abs/2102.08343

ICL

Learning invariant representations using Inverse Contrastive Loss

ISBI2020

kPF-flow

nueroqa

Nystromformer

panel_me_ode

A Variational Approximation for Analyzing the Dynamics of Panel Data

Pre-processing-T1-Weighted-MRI-Data

SPD-SRU

This is the code for the paper Statistical Recurrent Models on Manifold valued Data

spgru-uai19

tucker-conv

PyTorch Implementation of Tucker Convolution Layers

W2MHS

Wisconsin White Matter Hyperintensities Segmentation Toolbox

YOSO