| [02/07/2021] |
Motonobu Kanagawa led the discussion on the paper “A General Framework for Updating Belief Distributions” (Journal of Statistical Society, Series B) by P. G. Bissiri, C. Holmes and S. Walker. |
[PDF] |
| [24/06/2021] |
Pietro Michiardi led the discussion on the paper “Score-Based Generative Modeling through Stochastic Differential Equations” (ICLR 2021) by Y. Song et al. |
[PDF] |
| [10/06/2021] |
Giulio Franzese led the discussion on the paper “On Dissipative Symplectic Integration with Applications to Gradient-based Optimization” (Journal of Statistical Mechanics, 2021) by G. Franca, M. I. Jordan and R. Vidal. |
[PDF] |
| [03/06/2021] |
Maurizio Filippone led the discussion on the paper “Approximate Bayesian Inference for Latent Gaussian Models by Using Integrated Nested Laplace Approximations” (Journal of the Royal Statistical Society, Vol.71, 2009) by H. Rue, S. Martino and N. Chopin. |
[PDF] |
| [15/04/2021] |
Dimitrios Milios led the discussion on the paper “Robustness of Bayesian Neural Networks to Gradient-Based Attacks” (NeurIPS 2020) by G. Carbone et al. |
[PDF] |
| [18/03/2021] |
Julien Audibert led the discussion on the paper “The Lottery Ticket Hypothesis. Finding Sparse, Trainable Neural Networks” (ICLR 2019) by J. Frankle and M. Carbin. |
[PDF] |
| [04/03/2021] |
Ba-Hien Tran led the discussion on the paper “Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC” (AISTATS 2021) by P. Jaini, D. Nielsen and M. Welling. |
[PDF] |
| [25/02/2021] |
Bogdan Kozyrskiy led the discussion on the paper “Black Box Variational Inference” (AISTATS 2014) by R. Ranganath, S. Gerrish and D. M. Blei. |
[PDF] |
| [18/02/2021] |
Lucas Pascal led the discussion on the paper “Gradient Surgery for Multi-Task Learning” (NeurIPS 2020) by T. Yu et al. |
[PDF] |
| [11/02/2021] |
Maurizio Filippone led the discussion on the paper “Informative Bayesian Neural Network Priors for Weak Signals” (Bayesian Analysis) by T. Cui, A. Havulinna, P. Marttinen and S. Kaski. |
[PDF] |
| [12/01/2021] |
Rosa Candela led the discussion on the paper “Fluctuation-dissipation relations for stochastic gradient descent” (ICLR 2019) by S. Yaida. |
[PDF] |
| [15/12/2020] |
Ugo Lecerf led the discussion on the paper “Improving Generalization in Meta Reinforcement Learning using Learned Objectives” (ICLR 2020) by L. Kirsch, S. v. Steenkiste and J. Schmidhuber. |
[PDF] |
| [07/12/2020] |
Matthieu Da Silva–Filarder led the discussion on the paper “Target-Embedding Autoencoders for Supervised Representation Learning” (ICLR 2020) by D. Jarrett and M. v. d. Schaar. |
[PDF] |
| [01/12/2020] |
Pietro Michiardi led the discussion on the paper “Semi-Supervised Classification with Graph Convolutional Networks” (ICLR 2017) by T. Kipf and M. Welling. |
[PDF] |
| [26/11/2020] |
Motonobu Kanagawa led the discussion on the paper “Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences” (Preprint ArXiV) by M. Kanagawa, P. Hennig, D. Sejdinovic and B. K. Sriperumbudur. |
[PDF] |
| [19/11/2020] |
Gia-Lac Tran led the discussion on the paper “The Deep Weight Prior” (ICLR 2019) by A. Atanov et al. |
[PDF] |
| [12/11/2020] |
Giulio Franzese led the discussion on the paper “FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models” (ICLR 2019) by W. Grathwohl et al. |
[PDF] |
| [29/10/2020] |
Graziano Mita led the discussion on the paper “CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models” (Preprint ArXiV) by M. Yang et al. |
[PDF – Slides] |
| [22/10/2020] |
Dimitrios Milios led the discussion on the paper “Deep Gaussian Processes with Importance-weighted Variational Inference” (ICML 2019) by H. Salimbeni, V. Dutordoir, J. Hensman and M. Deisenroth. |
[PDF] |
| [24/09/2020] |
Alix Lhéritier led the discussion on the paper “Deep Optimal Stopping” (JMLR 2019) by S. Becker, P. Cheridito and A. Jentzen. |
[PDF] |
| [17/09/2020] |
Simone Rossi led the discussion on the paper “Efficiently sampling functions from Gaussian process posteriors” (ICML 2020) by J. Wilson et al. |
[PDF] |
| [10/09/2020] |
Davit Gogolashvili led the discussion on the paper “Generalization Properties of Learning with Random Features” (NeurIPS 2017) by A. Rudi and L. Rosasco. |
[PDF] |