IdanAchituve's Stars
WeiHongLee/Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning
facebookresearch/riemannian-fm
code for "Riemannian Flow Matching on General Geometries".
atong01/conditional-flow-matching
TorchCFM: a Conditional Flow Matching library
rrtucci/texnn
Python script that genetates LaTex code that draws a Neural Net as a causal DAG (Bayesian Network). Python wrapper for xy-pic LaTeX package.
median-research-group/LibMTL
A PyTorch Library for Multi-Task Learning
ssi-research/BayesAgg_MTL
Code that accompanies the paper Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning - Accepted to ICML2024
dvirsamuel/FPI
Code for our paper "Fixed-point Inversion for Text-to-image diffusion models"
nik-dim/pamal
Official repository of "Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models" [ICML 2023]
IdanAchituve/GDKL
Code that accompanies the paper Guided Deep Kernel Learning
AdamCobb/hamiltorch
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
dvirsamuel/SeedSelect
Code for our papers : "Generating images of rare concepts using pre-trained diffusion models" (AAAI 24) and "Norm-guided latent space exploration for text-to-image generation" (Neurips 23)
philipphennig/NumericsOfML
Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen
TeaPearce/Conditional_Diffusion_MNIST
Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.
AvivNavon/DWSNets
Official implementation for Equivariant Architectures for Learning in Deep Weight Spaces [ICML 2023]
themrzmaster/git-re-basin-pytorch
Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch
cobypenso/functional_ensemble_distillation
y0ast/DUE
Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
IdanAchituve/pFedGP
Code for Personalized Federated Learning with Gaussian Processes
manzilzaheer/DeepSets
google/neural-tangents
Fast and Easy Infinite Neural Networks in Python
brain-research/nngp
Deep neural network kernel for Gaussian process
aiola-lab/corener
Multi-task model for named-entity recognition, relation extraction, entity mention detection and coreference resolution.
activatedgeek/svgd
PyTorch implementation of Stein Variational Gradient Descent
hellerguyh/SGLDLoss
bayesiains/nflows
Normalizing flows in PyTorch
bayesiains/nsf
Code for Neural Spline Flows paper
google-research/hyperbo
Pre-trained Gaussian processes for Bayesian optimization
roboticcam/machine-learning-notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接
nayeemrizve/ups
"In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah (ICLR 2021)
KaiyangZhou/Dassl.pytorch
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.