AMLab Seminar

Weekly talks at AMLab given by internal and external speakers.

2017

Date Time Room Speaker Title (Link)
Jan 3 - - - Christmas break
Jan 10 - - - No talk
Jan 17 - - - IvI nieuwjaarsborrel
Jan 24 16:00-17:00 C3.163 Marco Loog Semi-Supervision, Surrogate Losses, and Safety Guarantees
Jan 31 16:00-17:00 C3.163 Max Welling AMLAB/QUVA's progress in Deep Learning
Feb 7 16:00-17:00 C3.163 Thijs van Ommen Recognizing linear structural equation models from observational data
Feb 14 16:00-17:00 C3.163 Jakub Tomczak Improving Variational Auto-Encoders using volume-preserving flows: A preliminary study
Feb 21 16:00-17:00 C3.163 Artem Grotov Deep Counterfactual Learning
Feb 28 16:00-17:00 C3.163 ChangYong Oh High dimensional Bayesian Optimization
Mar 7 16:00-17:00 C3.163 Karen Ullrich Soft Weight-Sharing for Neural Network Compression
Mar 14 16:00-17:00 C3.163 Taco Cohen Group Equivariant & Steerable CNNs
Mar 21 16:00-17:00 C3.163 Frederick Eberhardt Causal Macro Variables
Mar 28 - - - No talk
Apr 4 16:00-17:00 C3.163 Tineke Blom Causal Discovery in the Presence of Measurement Error
Apr 11 16:00-17:00 C3.163 Rianne van den Berg Graph convolutional networks as recommender systems
Apr 18 16:00-17:00 C3.163 Philip Versteeg Prediction and validation of causal effects in gene knockout experiments
Apr 25 - - - No talk due to ICLR
May 2 16:00-17:00 C3.163 Zeynep Akata Vision and Language for Multimodal Deep Learning
May 9 16:00-17:00 C3.163 Raghavendra Selvan Segmenting Tree Structures with Probabilistic State-space Models and Bayesian Smoothing
May 16 16:00-17:00 C3.163 Tim van Erven MetaGrad: Multiple Learning Rates in Online Learning
May 23 16:00-17:00 C3.163 Joris Mooij Causal Transfer Learning with Joint Causal Inference
May 30 16:00-17:00 C3.163 Maurice Weiler Learning steerable filters for rotation-equivariant CNNs
Jun 6 16:00-17:00 C3.163 Ted Meeds Integrating Cancer Genomics Data using Autoencoders
Jun 13 16:00-17:00 C3.163 Vaishak Belle Open-Universe Probabilistic Models
Jun 20 - - - No talk
Jun 27 - - - No talk
Jul 4 16:00-17:00 C3.163 Arnout Tilgenkamp (Flow Traders) Machine learning at Flow Traders: Past, Present, Future
- - - - No talks during summer
Sep 5 16:00-17:00 C3.163 Patrick Forré Markov Properties for Probabilistic Graphical Models with Latent Confounding and Feedback Loops
Sep 12 - - - No talk
Sep 19 16:00-17:00 C3.163 Stephan Bongers Marginalization of Structural Causal Models with feedback
Sep 26 - - - No talk
Oct 3 16:00-17:00 C3.163 Christos Louizos Bayesian Uncertainty and Compression for Deep Learning
Oct 10 16:00-17:00 C3.163 Peter O'Connor Towards Event-Based online Learning
Oct 17 - - - No talk
Oct 24 16:00-17:00 C3.163 Sara Magliacane  Joint Causal Inference from Observational and Experimental Datasets
Oct 31 16:00-17:00 C3.163 Elise van der Pol Graph-based Sequential Decision Making Under Uncertainty
Nov 7 16:00-17:00 C3.163 Matthias Reisser Failure Modes of distributed Variational Inference
Nov 14 16:00-17:00 C3.163 Thomas Kipf End-to-end learning on graphs with graph convolutional networks
Nov 21 - - - No talk
Nov 28 16:00-17:00 C3.163 Open slot Open slot
Dec 5 - - - No talk due to Sinterklaas (and also NIPS)
Dec 12 16:00-17:00 C3.163 Giorgio Patrini TBA
Dec 19 16:00-17:00 C3.163 Open slot Open slot

Archived Talks

Google Calendar

Contact: Thijs van Ommen (M[dot]vanOmmen[at]uva[dot]nl)