Seminář strojového učení a modelování / Machine Learning and Modelling Seminar

čtvrtek / Thursday 14:00
posluchárna / room S7
Malostranské náměstí 2

Společný seminář katedry teoretické informatiky a matematické logiky MFF UK a oddělění umělé inteligence ústavu informatiky AV ČR

Organized jointly by the Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathemeatics and Physics of the Charles University, and by the Department of Artificial Intelligence, Institute of Computer Science of the Czech Academy of Sciences

Kontakt: / Contact:
Martin Holeňa
www.cs.cas.cz/~martin
+420 266 052 921
martin@cs.cas.cz
skype martinholena

 

Na semináři ve čtvrtek 28. března budeme mít hosta z Vídně. / At the seminar on Thursday, March 28, we shall have a guest from Vienna.

Program:

Simon Rittel. Bayesian causal structure learning

Simon will review recent progress in the field of causal structure learning, with focus on Bayesian methods incorporating probabilistic prior knowledge, such as parametrized probability distribution over DAGs, variational inference and Gumbel-Softmax reparametrization trick.

 

Přehled seminářů v roce 2024 / List of seminars in 2024

23.  5.

Pierre Nicolay

Kinematic-aware Neural Network for Dynamics Modeling

25.  4.

Balint Gyevnar

How do we make explainable AI work for people?

11.  4.

Alex Goodall

Theory and Applications of Approximate Model-based Shielding for Safe Reinforcement Learning

28.  3.

Simon Rittel

Bayesian causal structure learning

14.  3.

Oliver Sutton

Can adversarial robustness be certified for classifiers learning high dimensional data?

pdf

29.  2.

Michal Znależniak

Contrastive hierarchical clustering

pdf

 1.  2.

Tomáš Pevný

Tractable probabilistic models for hierarchical data

pdf

 

Přehled seminářů v roce 2023 / List of seminars in 2023

 7. 12.

Klára Janoušková

Test-time adaptation

pdf

23. 11.

Patric Feldmeier

Neatest - neuroevolution-based generation of adaptive tests

pdf

 9. 11.

Felix Gemeinhardt

Quantum computing - from fundamentals to first quantum algorithms

pdf

26. 10.

Milan Straka

Optimization of deep neural networks

pdf,mov

12. 10.

Anton Bushuiev

Designing protein-protein interactions with self-supervised geometric deep learning

pdf

11.  5.

Rudolf Rosa

Generating texts with transformer-based large language models

pdf

27.  4.

Pavel Hrabák

Agents heterogeneity in microscopic models of pedestrian flow

pdf

13.  4.

Pierre Onghena

Comparing user perception of explanations developed with XAI methods

pdf

30.  3.

Thomas Seidelmann

Advanced multi-objective facility layout planning for modern manufacturing environments

pdf

16.  3.

Ondřej Podsztavek

Active domain adaptation and astronomy

pdf

 2.  3.

Adéla Šubrtová

Semantic editation of images

pdf

16.  2.

Dario Simionato

Exploiting causality methods for knowledge discovery from observational data

pdf

 5.  1.

Tomáš Kerepecký

An introduction to neural fields in computer vision and image processing

pdf

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