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hood

Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization

householderdice

icl-task-diversity

Code for the paper "Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression"

ilvr_adm

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral)

imold

Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)

imp_bias_control

Code for reproducing experiments in "Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States""

improved-hyperparameter-learning

Codes for 'Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models' (ICML 2023)

incompletelu.jl

Crout ILU for Julia

inferchange

Multiscale Covariance Scanning and related Algorithms

inference_denoising_mri_recon

Office code for "Inference Stage Denoising for Undersampled MRI Reconstruction"

information-theoretic-safe-exploration

Information-Theoretic Safe Exploration with Gaussian Processes

injectivity_relu_layer

This repository contains the code of the paper "Injectivity of ReLU networks: a statistical physics perspective".

inpaintingnmf

This is the accompanying repository for the article Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization authored by Ondřej Mokrý, Paul Magron, Thomas Oberlin and Cédric Févotte, submitted to Elsevier Signal Processing.

invokeai

InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.

ircnn

Learning Deep CNN Denoiser Prior for Image Restoration (CVPR, 2017) (Matlab)

isit_2020_hgf

isl

Training Implicit Generative Models via an Invariant statistical loss (ISL)

isrrr

Integrative Sparse Reduced-Rank Regression for Analysis of High-Dimensional Multi-Omics Data

iterativesolvers.jl

Iterative algorithms for solving linear systems, eigensystems, and singular value problems

jadce

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

jax-sysid

A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax

jmmle_code

kalman.jl

Flexible filtering and smoothing in Julia

l-greco

AN EFFICIENT AND GENERAL FRAMEWORK FOR LAYERWISE-ADAPTIVE GRADIENT COMPRESSION

lar

AR extension of ForneyLab.jl

latex-paper-templates

Latex-format paper templates, including Elsevier, arXiv and IEEE Access.

lcsia

Learned Compressed Sensing Iterative Algorithms

ld-gamp

Implement of LD-GAMP

ldamp_based-channel-estimation

This code is for the following paper: H. He, C. Wen, S. Jin, and G. Y. Li, “Deep learning-based channel estimation for beamspace mmwave massive MIMO systems,” IEEE Wireless Commun. Lett., vol. 7, no. 5, pp. 852–855, Oct. 2018.