Machine Learning: cours avancé

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Le but de ce cours est d’approfondir vos compétences en Machine Learning, en implémentant des articles scientifiques. Nous avons l’ambition de vous propulser dans le top 5% des praticiens en Machine Learning, afin de booster vos opportunités professionnelles. Articles implémentés (ou prochainement implémentés): Maxout Networks Auto-Encoding Variational Bayes Generative Adversarial Networks Conditional Generative Adversarial Nets NICE: Non-linear Independent Components Estimation Variational Inference with Normalizing Flows Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Adversarially Learned Inference Improved Techniques for Training GANs Least Squares Generative Adversarial Networks Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Adversarial Feature Learning On First-Order Meta-Learning Algorithms Sequential Neural Likelihood Optimizing Millions of Hyperparameters by Implicit Differentiation Implicit Neural Representations with Periodic Activation Functions Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Likelihood-free MCMC with Amortized Approximate Ratio Estimators Ne RF: Representing Scenes as Neural Radiance Fields for View Synthesis Multiplicative Filter Networks Gromov-Wasserstein Distances between Gaussian Distributions Playing Atari with Deep Reinforcement Learning Human-level control through deep reinforcement learning Proximal Policy Optimization Algorithms Adam: A Method for Stochastic Optimization Wasserstein GANDeep Unsupervised Learning using Nonequilibrium Thermodynamics Instant Neural Graphics Primitives with a Multiresolution Hash Encoding Auto Int: Automatic integration for fast neural volume rendering Mip-Ne RF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields Masked Autoregressive Flow for Density Estimation Density estimation using Real NVPNeural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference N’attendez plus avant d’affûter vos compétences en Machine Learning!