Videos

Physics ML Workshop

Reinforcement Learning, Control, and Inference

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Reinforcement Learning for Materials Synthesis

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Noise2Self: Blind Denoising by Self-Supervision

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Spectral Inference Networks: Unifying Deep and Spectral Learning

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Physics-constrained Computational Imaging

ML4Science
Wednesday, May 29, 2019 Laura Waller
Physics ML Workshop

Session Panel: Generative Models

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Hybrid Physical - Deep Learning Models for Astronomical Inverse Problems

ML4Science
Wednesday, May 29, 2019 François Lanusse
Physics ML Workshop

Towards a cosmology emulator using Generative Adversarial Networks

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Improved learning for materials and chemical structures through symmetry, hierarchy and similarity

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Deducing Inference from Hyperspectral Imaging of Materials Using Deep Recurrent Neural Networks

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Putting Non-Euclidean Geometry to Work in ML: Hyperbolic and Product Manifold Embeddings

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Flow-based generative models for lattice field theory

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Generative models as priors for signal denoising

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Session Panel: Incorporating Physics directly into the Models

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Cosmology for Machine Learning

ML4Science
Wednesday, May 29, 2019 Uros Seljak
Physics ML Workshop

Physics Constrained Fluid Flow Prediction using Lyapunov's Method

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

FPGA-accelerated machine learning inference as a service for particle physics computing

ML4Science
Wednesday, May 29, 2019
Phys ML Workshop

Machine learning in high-energy particle physics experiments, from simulation, through reconstruction to physics analysis

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Physics informed Machine Learning

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Machine learning for lattice gauge theory

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Session Panel: Producing & Discovering Dynamical Models

ML4Science
Wednesday, May 29, 2019
Physics ML Workshop

Solving Astrophysical PDEs with Deep Neural Networks and TensorFlow

ML4Science
Wednesday, May 29, 2019

Data Driven Discretization for Partial Differential Equations

ML4Science
Wednesday, May 29, 2019

Learning physical interaction in many ways

ML4Science
Wednesday, May 29, 2019

AI Feynman: a Physics-Inspired Method for Symbolic Regression

ML4Science
Wednesday, May 29, 2019
Physics & ML Workshop

Data-driven methods for the discovery of governing equations

ML4Science
Wednesday, May 29, 2019

Welcome and Introductory Remarks - Physics in Machine Learning Workshop

ML4Science
Wednesday, May 29, 2019
Claudia von Vacano and Chris Kennedy at the podium

Hate speech, algorithms, and digital connectivity

Lecture
Wednesday, May 8, 2019 Chris Kennedy
Shreeharsh Kelkar at the podium

Reinventing Expertise in the Age of Platforms: The Case of Data Science

Lecture
Wednesday, May 1, 2019
Microsoft underwater data center

Microsoft Azure and Microsoft Research: advancing cloud computing together

Lecture
Monday, April 22, 2019

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