AMLab Seminar

Weekly talks at AMLab given by internal and external speakers.

2019 — spring

Date Time Room Speaker Title (Link to abstract)
Mar 14 16:00-17:00 C3.163 Changyong Oh Combinatorial Bayesian Optimization using Graph Representations
Feb 28 16:00-17:00 C3.163 Christos Louizos Learning Exchangeable Distributions
Feb 21 16:00-17:00 C3.163 Thomas Kipf Compositional Imitation Learning: Explaining and executing one task at a time
Feb 14 16:00-17:00 C3.163 Victor Garcia GRIN: Graphical Recurrent Inference Networks
Feb 7 - - - No talk
Jan 31 16:00-17:00 C3.163 Emiel Hoogeboom Emerging Convolutions for Generative Normalizing Flows
Jan 24 - - - No talk
Jan 17 16:00-17:00 C3.163 Herke van Hoof Learning Selective Coverage Strategies for Surveying and Search
Jan 10 - - - No talk

2018 — fall
Starting in September, the seminar will normally be held on Thursdays instead of Tuesdays.

Date Time Room Speaker Title (Link to abstract)
Dec 20 - - - No talk
Dec 13 16:00-17:00 C3.163 Tom Claassen Causal discovery from real-world data: relaxing the faithfulness assumption
Dec 6 - - - No talk (NeurIPS)
Nov 29 16:00-17:00 C3.163 Daniel Worrall Semigroup Convolutional Neural Networks: Merging Scale-space and Deep Learning
Nov 22 16:00-17:00 C3.163 Maurice Weiler 3D Steerable CNNs
Nov 12 11:00-12:00 C3.163 Peter Orbanz Statistical models of large graphs and networks
Nov 8 16:00-17:00 C3.163 Wendy Shang Channel-Recurrent Autoencoding
Nov 1 16:00-17:00 C3.163 Stephan Alaniz Iterative Binary Decision
Oct 31 16:00-17:00 C3.163 Giorgio Patrini Sinkhorn AutoEncoders
Oct 25 16:00-17:00 C3.163 Kihyuk Sohn Deep Domain Adaptation in the Wild
Oct 18 16:00-17:00 C3.163 Shihan Wang Apply Machine Learning and Data Mining to Promote Physical Activity
Oct 11 16:00-17:00 C3.163 Patrick Forré Non-linear structural causal models with cycles and latent confounders
Oct 4 16:00-17:00 C3.163 Bela Mulder Pitting man against machine in the arena of bottom-up design of crystal structures
Sep 27 16:00-17:00 C3.163 Jakub Tomczak Deep Learning and Bayesian Inference for Medical Imaging
Sep 20 16:00-17:00 C3.163 Patrick van der Smagt Latent optimal control
Sep 13 - - - No talk (IvI scientific get-together)
Sep 11 15:00-16:00 C0.110 Cédric Archambeau Learning Representations for Hyperparameter Transfer Learning
Sep 6 16:00-17:00 C3.163 Joris Mooij Validating Causal Discovery Methods

Archived Talks

Google Calendar

Contact: Daniel Worrall (d[dot]e[dot]worrall[at]uva[dot]nl)