idanachituve Goto Github PK

auxilearn

Implementation of Auxiliary Learning by Implicit Differentiation

avivsham.github.io

cellular_automaton

visualize generations of 1D cellular automaton

cnn_using_numpy

Implementing CNN using only numpy

defrec_and_pcm

Self-Supervised Learning for Domain Adaptation on Point-Clouds

em_for_mixture_of_histograms

EM for Mixture of Histograms

fedocs

Code that accompanies the paper Communication Efficient Distributed Learning over Wireless Channels

first_gan

Simple GAN exercise

gdkl

Code that accompanies the paper Guided Deep Kernel Learning

gp-tree

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

guided-diffusion

idanachituve.github.io

kalman_filter

Simple kalman filter exercise.

lincongauss

Integrals of Gaussians under linear domain constraints

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

mrf

create a random picture from known MRF distribution. Afterwards, compare the true distribution vs the distribution according to Gibbs sampling as the number of iterations increase

multclass_with_ecoc

Multiclass classification with Error-Correcting-Output-Code

multiple_cause_model

a Multiple Cause Model

neural-network-from-scratch

Implementing a NN with numpy for classification of CIFAR10 images.

nn-basic-stuff

ocr_structured_prediction

using structured Perceptron for classifying the OCR dataset

pfedgp

Code for Personalized Federated Learning with Gaussian Processes

snli-re-read-lstm

sudoku_solver_with_genetic_algorithm

Using genetic algorithm to solve the game of sudko. The input is a matrix with 0 entries at the missing location and the output is the solved sudoku game

trl

word-tagging