ilkarman's Stars
jbhuang0604/awesome-computer-vision
A curated list of awesome computer vision resources
dmlc/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
cleanlab/cleanlab
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
tkipf/gcn
Implementation of Graph Convolutional Networks in TensorFlow
rtqichen/torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
cmhungsteve/Awesome-Transformer-Attention
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
facebookresearch/vissl
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.
phlippe/uvadlc_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
dair-ai/Transformers-Recipe
🧠 A study guide to learn about Transformers
JustGlowing/minisom
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
janosh/awesome-normalizing-flows
Awesome resources on normalizing flows.
wvangansbeke/Unsupervised-Classification
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
gpleiss/temperature_scaling
A simple way to calibrate your neural network.
Chen-Cai-OSU/awesome-equivariant-network
Paper list for equivariant neural network
StanfordVL/GibsonEnv
Gibson Environments: Real-World Perception for Embodied Agents
microsoft/Tutel
Tutel MoE: An Optimized Mixture-of-Experts Implementation
sunwj/CAR
Content adaptive resampler for image downscaling
KinglittleQ/torch-batch-svd
A 100x faster SVD for PyTorch⚡️
uclnlp/torch-imle
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
mfinzi/equivariant-MLP
A library for programmatically generating equivariant layers through constraint solving
brohrer/sharpened-cosine-similarity
An alternative to convolution in neural networks
sagelywizard/pytorch-mdn
Mixture Density Networks for PyTorch
pylayers/pylayers
PyLayers is a Python platform for Site Specific Radio Propagation Simulation for Evaluating Indoor Localization algorithms using UWB radio signals including Human Indoor Mobility
artest08/LateTemporalModeling3DCNN
hollance/reliability-diagrams
Reliability diagrams visualize whether a classifier model needs calibration
giannisnik/som
Pytorch implementation of a Self-Organizing Map
ldecamp/fair_noise_as_targets
Implementation of the Unsupervised learning by predicting noise paper
locuslab/sdp_clustering
philipp-fischer/borescope
Borescope for Python