AMLab Seminar

Weekly talks at AMLab given by internal and external speakers.

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 16:00-17:00 C3.163 Herke van Hoof TBA
Dec 13 16:00-17:00 C3.163 Tom Claassen TBA
Dec 6 - - - No talk (NIPS)
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 TBA
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

2018 – spring

Date Time Room Speaker Title (Link)
Aug 28 16:00-17:00 C3.163 Tameem Adel On interpretable representations and the tradeoff between accuracy and interpretability
Jul 30 11:00-12:00 C3.163 Jesse Bettencourt Neural Ordinary Differential Equations
Jul 26 11:00-12:00 C1.112 Dmitry Vetrov Interesting properties of the variational dropout framework
Jun-Aug - - - No regular talks
May 29 16:00-17:00 C3.163 Diederik Roijers Multiple objectives: because we (should) care about the user
May 22 16:00-17:00 C3.163 Taco Cohen The Quite General Theory of Equivariant Convolutional Networks
May 15 16:00-17:00 C3.163 Emiel Hoogeboom G-HexaConv
May 8 - - - No talk
May 1 - - - No talk (ICLR)
Apr 24 16:00-17:00 C3.163 Zeynep Akata Representing and Explaining Novel Concepts with Minimal Supervision
Apr 17 16:00-17:00 C3.163 Tineke Blom Causal Modeling for Dynamical Systems using Generalized Structural Causal Models
Apr 10 16:00-17:00 F1.02 Petar Veličković Keeping our graphs attentive
Apr 9 16:00-17:00 C1.112 Avital Oliver Realistic Evaluation of Semi-Supervised Learning Algorithms
Apr 3 16:00-17:00 C3.163 Karen Ullrich Variational Bayes Wake-Sleep algorithm for expressive latent representations in 3D protein reconstruction
Mar 27 16:00-17:00 C3.163 Wouter Kool Attention Solves Your TSP
Mar 20 16:00-17:00 C3.163 Paul Baireuther Quantum Error Correction with Recurrent Neural Networks
Mar 13 16:00-17:00 C1.112 Max Welling Stochastic Deep Learning
Mar 6 16:00-17:00 C3.163 Thijs van Ommen Accurate and efficient causal discovery
Feb 27 - - - No talk
Feb 20 16:00-17:00 C3.163 Bas Veeling Uncertainty in Deep Neural Networks with Stochastic Quantized Activation Variational Inference
Feb 13 16:00-17:00 C3.163 ChangYong Oh BOCK: Bayesian Optimization with Cylindrical Kernels
Feb 6 - - - No talk
Jan 30 16:00-17:00 C3.163 Jorn Peters Binary Neural Networks: an overview
Jan 26 15:30-16:30 C3.163 Veronika Cheplygina Challenges of multiple instance learning in medical image analysis
Jan 16 16:00-17:00 C3.163 Jakub Tomczak Attention-based Deep Multiple Instance Learning

Archived Talks

Google Calendar

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