News

RIKEN's Programs for Junior Scientists

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January 30, 2023

Our work “SAM as an Optimal Relaxation of Bayes” (T. Moellenhoff and M. E. Khan) is accepted at ICLR 2023 (notable top 5%). We have another paper “The Lie-Group Bayesian Learning Rule” (E. M. Kiral, T. Moellenhoff, M.E. Khan) accepted at AISTATS 2023.


January 20, 2023

Happy Buzaaba is co-organizing the ICLR2023 workshop on AfricaNLP to be held on 5th May in Kigali, Rwanda.


December 12, 2022

We organized the “Continual Lifelong Learning Workshop” at ACML2022 in Hyderabad, India.


December 08, 2022

Invited Prof. Michael Choi (National University of Singapore and Yale-NUS College) for a seminar talk. Title “From reversiblizations of non-reversible Markov chains to landscape modification”.


December 03, 2022

Emtiyaz Khan gave an invited talk at NeurIPS 2022 Workshop on Broadening Research Collaborations in Machine Learning [Slides].


November 24, 2022

Emtiyaz Khan gave an invited talk at University of Bath in Prof. Olga Isupova’s group [Slides].


November 09, 2022

Today, we hosted Prof. Yarin Gal for a seminar on “Uncertainty in Deep Learning: Lessons Learned from Medical Imaging”.


November 01, 2022

The ABI team is organizing a seminar on Tuesday, November 1st.


October 25, 2022

Forthcoming talks by Geoffrey Wolfer:

  • [16 Nov, 2022] [ CCSP Seminar ] Talk: "Geometric Aspects of Markov Models"
  • [22 Nov, 2022] [ IBIS'22 ] Poster: "Variance-Aware Estimation of Kernel Mean Embedding"
  • [1 Dec, 2022] [ SITA'22 ] Talk: "Markovian Embeddings of Markov Chains"

October 24, 2022

Pierre will visit Toulouse School of Economics as an invited researcher in November. He will give a series of 5 lectures at on PAC-Bayes and Mutual Information bounds, on Nov. 8, 15, 21, 22 and 28. The lectures are intended for PhD students but will be also opened for master students. They will be essentially based on User-friendly introduction to PAC-Bayes bounds. He will also give the following talks:


September 02, 2022

Forthcoming talks by Geoffrey Wolfer:

  • [19 Sep, 2022] [ IG4DS ] Talk: "Information Geometry of Reversible Markov Chains" [ Slides ] [ Video ]
  • [20 Sep, 2022] [ IG4DS ] Talk: "Geometric Aspects of Data-Processing of Markov Chains" [ Slides ] [ Video ]
  • [26 Sep, 2022] [ BIID'10 ] Talk: "Geometric Aspects of Data-Processing of Markov Chains"

August 24, 2022

Forthcoming talk by Pierre:


May 26, 2022

[ ENTROPY ] special issue on Approximate Bayesian Inference (edited by Pierre) is now available as a book and as a pdf file that can be downloaded for free on the editor website: [ Book page ]


May 01, 2022

Recent talks by Pierre:

  • [20 Jan, 2022] StatML CDT seminar (Imperial & Oxford): "Matrix factorization for time series analysis" [ Slides ]
  • [02 Feb, 2022] Invited talk at [ AABI2022 ] "What to expect from PAC-Bayes bounds" [ Slides ] [ Video ]
  • [03 Mar, 2022] RIKEN AIP High-dimensional modelling team seminar: "Deviation inequalities for Markov chains" [ Slides ] [ Video ]
  • [19 Apr, 2022] [ DELTA ] Seminar: "PAC-Bayes bounds and contraction of the posterior"
  • [21 Apr, 2022] [ International Bayes Club ] Seminar: "PAC-Bayes bounds and contraction of the posterior"
  • [28 Apr, 2022] [ One World ABC ] Seminar: "Concentration and robustness of discrepancy-based ABC" [ Slides ] [ Video ]

Forthcoming talks:


March 30, 2022

Emtiyaz Khan gave the following talks in March and Feb, 2022


December 08, 2021

Emtiyaz Khan, Dharmesh Tailor and Siddharth Swaroop will be giving an invited talk on Adaptive and Robust Learning with Bayes at the NeurIPS 2021 Bayesian deep learning workshop on Dec. 14th 11:10 - 11:30 GMT.


December 06, 2021

We won both tracks of the NeurIPS competition on Approximate Inference in Bayesian Deep Learning! Please join our talks at the NeurIPS 2021 competition track (Dec. 9th, 6pm GMT) and at the BDL workshop (Dec. 14th, 4:40pm GMT) to learn about our solution.


October 22, 2021

On arXiv today: User-friendly introduction to PAC-Bayes bounds by P. Alquier


October 01, 2021

Our Bayes-duality project is launched with a funding of $2.76 million by JST-ANR’s CREST proposal


September 30, 2021

Invited talk by Pierre Alquier at AmLab (Amsterdam) on [MMD based estimation]


September 29, 2021

Two papers accepted at NeurIPS 2021:


September 28, 2021

Paper by Dimitri Meunier & Pierre Alquier accepted+published in Entropy: [Meta-strategy for Learning Tuning Parameters with Guarantees]


September 21, 2021

Invited talk by Emtiyaz Khan at Tübingen AI Center (Philipp Hennig’s group).


September 17, 2021

Invited talk by Emtiyaz Khan at Secondmind.


September 16, 2021

Invited talk by Emtiyaz Khan at Durham CDT Data Science Workshop.


September 13, 2021

Invited talk by Pierre Alquier at Ecology and Dependance 2021 (EcoDep) on [ Risk Bound for High Dimensional Time Series Completion ]


August 15, 2021

Invited talk by Emtiyaz Khan at KDD workshop 2021 Model Mining [ Slides ]


July 23, 2021

Invited talk by Emtiyaz Khan at Theory and Foundation of Continual Learning [ Slides ] [ SlidesLive Video ]


July 09, 2021

A new paper on Bayesian Learning Rule by M.E. Khan and H. Rue.


May 13, 2021

One paper accepted at UAI2021: Subset-of-Data Variational Inference for Deep Gaussian-Process Regression by A. Jain, P.K. Srijith, M.E. Khan.


May 10, 2021

Three papers were accepted at ICML2021:


March 10, 2021

16th AIP Open Seminar: talks by Approximate Bayesian Inference Team. Talks by


January 28, 2021

Two papers were accepted at AISTATS2021:


November 11, 2020

“Approximate Bayesian Inference”, the editorial of a forthcoming special issue in Entropy, written by P. Alquier, is now published: paper. You can submit a paper until the end of Feb. 2021. Special Issue on Approximate Bayesian Inference


November 05, 2020

The videos of two recent talks by Pierre Alquier are now online:


November 02, 2020

A series of seminars on “Bayesian principles for learning machines” held by Emtiyaz Khan will take place at the following dates and locations.


October 06, 2020

Pierre Alquier joined the editorial board of JMLR.


September 26, 2020

Our paper on continual learning by functional regularization on the memorable past is accepted as an oral presentation at NeurIPS 2020.


September 07, 2020

New preprint by Pierre Alquier on online learning with unbounded loss functions.


August 17, 2020

We have two tutorials at SMILES 2020! See Emtiyaz Khan’s tutorial on DL with Bayes (slides, video) and Pierre Alquier on Sequential Prediction Problems (video).


July 20, 2020

New tutorial by Emtiyaz Khan on DL with Bayes at SPCOM 2020. [slides] [video]


May 12, 2020

Emtiyaz Khan gave a talk on DNN2GP.


April 01, 2020

Emtiyaz Khan received a Kakenhi Grant (Series B) on “life-long learning” (approx. USD 158K).