Archived Talks

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

2017


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

2016


Date,Time,Room,Speaker,Title (Link)
Dec 27,-,-,-,Christmas break
Dec 20,16:00-17:00,C3.163,Open,Open
Dec 13,16:00-17:00,C3.163,Thomas Kipf,Deep Learning for Graph-Structured Data
Dec 6,-,-,-,No talk due to NIPS
Nov 29,16:00-17:00,C3.163,Sara Magliacane,Ancestral Causal Inference
Nov 22,16:00-17:00,C3.163,Paul Rubenstein,Structural Equation Models: Where do they come from?
Nov 16,16:00-17:00,C4.174,Tom Claassen,Causal discovery in psychometric data sets: handling deterministic relations
Nov 8,16:00-17:00,C3.163,Open,Open
Nov 1,16:00-17:00,C3.163,Open,Open
Oct 25,16:00-17:00,C3.163,Open,Open
Oct 18,16:00-17:00,C3.163,Open,Open
Oct 11,16:00-17:00,C3.163,Joan Bruna,Addressing Computational and Statistical Gaps with Deep Neural Networks
Aug 23,16:00-17:00,C3.163,Riaan Zoetmulder,
Deep Causal Inference
July 12,16:00-17:00,C3.163,Christios Louizos,Bayesian Deep Learning and Uncertainty
July 5,16:00-17:00,C3.163,Peter O’Connor,Deep Spiking Networks
June 28,16:00-17:00,C3.163,Tameem Adel,Collapsed Variational Inference for Sum-Product Networks
June 21,16:00-17:00,C3.163,Matthias Reisser,Distributed Bayesian Deep Learning
June 21,-,-,-,Cancelled
June 7,16:00-17:00,C3.163,Thijs van Ommen,Robust probability updating
May 31,16:00-17:00,C3.163,Matthijs Snel,
An introduction to market making and data science at Optiver
May 24,16:00-17:00,C4.174,Ted Meeds,
Likelihood-free Inference by Controlling Simulator Noise
May 17,16:00-17:00,C3.163,Karen Ullrich,Combining generative models and deep learning
May 10,16:00-17:00,C3.163,Stephan Bongers,Marginalization and Reduction of Structural Causal Models
May 3,16:00-17:00,C3.163,Patrick Putzky,Neural Networks for estimation in inverse problems
Apr 26,16:00-17:00,C3.163,Joris Mooij,Automating Causal Discovery and Prediction
Apr 19,16:00-17:00,C3.163,Yash Satsangi,Exploiting Submodular Value Functions for Scaling Up Active Perception
Apr 12,16:00-17:00,C3.163,Philip Versteeg,Causal inference and validation with micro-array data
Mar 8,16:00-17:00,C4.174,Sarod Yatawatta,Modern radio astronomy: challenges and opportunities
Mar 1,16:00-17:00,C3.163,Joao Messias,Variable-Order Markov Models for Sequence Prediction  (2/2)
Feb 23 ,16:00-17:00,C3.163,Joao Messias,Variable-Order Markov Models for Sequence Prediction (1/2)
Feb 16 ,16:00-17:00,C3.163,Mandar Chandorkar,Space Weather Prediction using Gaussian Process (GP) Non Linear Auto-Regressive Models
Feb 9 ,16:00-17:00,C3.163,Kyriacos Shiarli,Learning cost functions for Sample-based robotic planners
Jan 26 ,16:00-17:00,C3.163,Mijung Park,Bayesian methodologies for efficient data analysis
Jan 19 ,16:00-17:00,C3.163,Deepak Geetha Viswanathan,Generalized parts-based models for unrectified images
Jan 12 ,16:00-17:00,C3.163,Albert Huizing,Applying the art of deep learning to radar
Jan 5,-,-,-,Christmas break

2015


Date,Time,Room,Speaker,Title (Link)
Dec 29,-,-,-,Christmas break
Dec 22,-,-,-,Christmas break
Dec 15 ,16:00-17:00,C3.163,John Ashley Burgoyne,‘Big data’ music-cognition style
Dec 8,-,-,-,No talk due to NIPS
Dec 1 ,16:00-17:00,C3.163,Sara Magliacane,Probabilistic logical causal inference
Nov 24 ,16:00-17:00,C3.163,Artem Grotov,Self-learning search engines
Nov 17 ,16:00-17:00,C3.163,Antti Hyttinen,Constraint Satisfaction Approach to Causal Inference
Nov 10,-,-,-,Cancelled
Nov 3,-,-,-,Cancelled
Oct 27 ,16:00-17:00,C3.163,Yash Satsangi,Probably Approximately Correct Greedy Maximization
Oct 20 ,16:00-17:00,C3.163,Taco Cohen,Harmonic Exponential Families
Oct 13 ,13:00-14:00,C3.163,Sach Mukherjee,Towards empirical assessment of causal inference
Oct 6 ,-,-,-,Cancelled
Sep 29 ,16:00-17:00,C3.163,Elena Sokolova,Causal Discovery from Medical Data
Sep 22 ,16:00-17:00,C3.163,Video: Michael Jordan,On Computational Thinking: Inferential Thinking and Big Data
Sep 15,-,-,-,Opening QUvA Lab
Sep 8,-,-,-,Cancelled
Sep 1 ,15:00-16:00,C1.112,Joost Kok,Machine Learning in Scientific Applications

 

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