Seminar in Mathematics, Physics & Machine Learning

Videos found: 114.

Including videos from https://educast.fccn.pt/vod/channels/2qcyb7l1a1.

2023/09/22

Olga Mula

*Optimal State and Parameter Estimation Algorithms and Applications to Biomedical Problems*

2023/05/18

Rui Castro

*Anomaly detection for a large number of streams: a permutation/rank-based higher criticism approach*

2023/05/11

Harry Desmond

*Exhaustive Symbolic Regression (or how to find the best function for your data)*

2023/05/04

Diogo Gomes

*Mathematics for data science and AI - curriculum design, experiences, and lessons learned*

2023/04/27

Paulo Rosa

*Deep Reinforcement Learning based Integrated Guidance and Control for a Launcher Landing Problem*

2023/04/20

Rongjie Lai

*Learning Manifold-Structured Data using Deep Neural Networks: Theory and Applications*

2023/03/09

Gonçalo Correia

*Learnable Sparsity and Weak Supervision for Data-Efficient, Transparent, and Compact Neural Models*

2023/01/19

Alhussein Fawzi

*Discovering faster matrix multiplication algorithms with deep reinforcement learning*

2022/12/15

Bruno Loureiro

*Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks*

2022/11/24

Markus Reichstein

2022/11/03

Frederico Fiuza

*Accelerating the understanding of nonlinear dynamical systems using machine learning*

2022/03/24

Fernando E. Rosas

*Towards a deeper understanding of high-order interdependencies in complex systems*

2022/01/20

Anders Hansen

2021/11/04

George Em Karniadakis

*Operator regression via DeepOnet: Theory, Algorithms and Applications*

2021/07/09

Usman Khan

*Distributed ML: Optimal algorithms for distributed stochastic non-convex optimization*

2021/06/25

Yuejie Chi

*Policy Optimization in Reinforcement Learning: A Tale of Preconditioning and Regularization*

2021/06/18

Ruth Misener

*Partition-based formulations for mixed-integer optimization of trained ReLU neural networks*

2021/05/21

Kyriakos Vamvoudakis

2021/04/09

Pedro A. Santos

2021/03/17

Hsin Yuan Huang, (Robert)

*Information-theoretic bounds on quantum advantage in machine learning*

2021/03/03

A. Pedro Aguiar

2021/02/10

Caroline Uhler

*Causal Inference and Overparameterized Autoencoders in the Light of Drug Repurposing for SARS-CoV-2*

2021/02/03

Miguel Couceiro

*Making ML Models fairer through explanations, feature dropout, and aggregation*

2020/12/09

Samantha Kleinberg

*Data, Decisions, and You: Making Causality Useful and Usable in a Complex World*

2020/12/02

Gitta Kutyniok

*Deep Learning meets Physics: Taking the Best out of Both Worlds in Imaging Science*

2020/11/25

Tommaso Dorigo

*Dealing with Systematic Uncertainties in HEP Analysis with Machine Learning Methods*

2020/11/20

Carola-Bibiane Schönlieb

2020/07/30

Masoud Mohseni

*TensorFlow Quantum: An open source framework for hybrid quantum-classical machine learning*

2020/06/25

Csaba Szepesvári

*Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting*

2020/06/11

Marcelo Pereyra

*Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau*

2020/05/21

André David Mendes