ML course - EPFL Machine Learning Course, Fall 2021

Last update: Jan 04, 2023

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Overview

EPFL Machine Learning Course CS-433

Machine Learning Course, Fall 2021

Repository for all lecture notes, labs and projects - resources, code templates and solutions. Videos available here on youtube.

The course website and syllabus is available here: https://www.epfl.ch/labs/mlo/machine-learning-cs-433/

Contact us if you have any questions, via the discussion forum (password on moodle for EPFL students), or email to the assistants or teachers. Please create issues and pull requests here using the menu above.

Owner

EPFL Machine Learning and Optimization Laboratory

GitHub Repository https://www.epfl.ch/labs/mlo/machine-learning-cs-433/

Deep Structured Instance Graph for Distilling Object Detectors (ICCV 2021)

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Code release for Local Light Field Fusion at SIGGRAPH 2019

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The pytorch implementation of SOKD (BMVC2021).

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Segmentation-Aware Convolutional Networks Using Local Attention Masks

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Face recognition. Redefined.

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Code for BMVC2021 paper "Boundary Guided Context Aggregation for Semantic Segmentation"

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Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology

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Part-aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking

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172 Dec 27, 2022

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!

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No Code AI/ML platform

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Code examples and benchmarks from the paper "Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective"

Code For the Paper "Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective" Author: Robert Bamler Date: 22 D

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Evaluating saliency methods on artificial data with different background types

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Pytorch implementation of AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks

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Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

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471 Dec 16, 2022