Research seminars

Our virtual seminar series is where we exchange ideas with guest speakers, keeping you up to date with the latest developments and inspiring research topics. Occasionally, Secondmind researchers present their own work as well.

Upcoming seminars

Mickael Binois

June 27, 2024 - Mickael Binois - Inria
Personal website

Kerstin Eder

July, 2024 - Kerstin Eder - University of Bristol

Andreas Bender

September 19, 2024 - Andreas Bender - University of Cambridge
Personal website

Past seminars

Ilija Bogunovic - From Data to Confident Decisions: Robust and Efficient Algorithmic Decision Making

June 13, 2024 - Ilija Bogunovic - University College London
Personal website

Dario Azzimonti - Preference learning with Gaussian processes

May 23, 2024 - Dario Azzimonti - IDSIA
Personal website

Mojmír Mutný - Optimal Experiment Design in Markov Chains

March 28, 2024 - Mojmír Mutný - ETH Zurich
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Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management

October 26, 2023 - Domenic Di Francesco - The Alan Turing Institute
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Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering

July 6, 2023 - Antonio Del Rio Chanona - Imperial College London
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Luigi Nardi - Harnessing new information in Bayesian optimization

June 7, 2023 - Luigi Nardi - Lund University, Stanford University and DBtune (www.dbtune.ai)
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Christopher Nemeth - Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates

February 23, 2023 - Christopher Nemeth - Lancaster University.
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David K. Duvenaud - A farewell to GPs

December 14, 2022 - David K. Duvenaud - University of Toronto.
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Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling: the geoML project

November 23, 2022 - Ítalo Gomes Gonçalves - Universidade Federal do Pampa
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Martin Jørgensen - Bézier Gaussian Processes

November 10, 2022 - Martin Jørgensen - University of Oxford
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Barbara Rakitsch - Interacting ODEs with Gaussian Processes

October 6, 2022 - Barbara Rakitsch - Bosch AI
Details

Sebastian Farquhar - Unbiased Active Learning and Testing

September 16, 2022 - Sebastian Farquhar - University of Oxford
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Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes

June 23, 2022 - Pablo Moreno-Muñoz - Technical University of Denmark
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Aryan Deshwal - Bayesian Optimization over Combinatorial Structures

May 26, 2022 - Aryan Deshwal - Washington State University.
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François-Xavier Briol - Bayesian Estimation of Integrals: A Multi-task Approach

January 6, 2021 - François-Xavier Briol - Lecturer in the Department of Statistical Science at University College London, Group Leader at The Alan Turing Institute
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Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes

December 2, 2021 - Dino Sejdinovic - Associate Professor at the Department of Statistics, University of Oxford, a Fellow of Mansfield College, Oxford, and a Turing Fellow of the Alan Turing Institute
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Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning

November 25, 2021 - Noémie Jaquier - Postdoctoral researcher at Karlsruhe Institute of Technology
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François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints

November 25, 2021 - François Bachoc - Assistant professor in statistics at the Toulouse Mathematics Institute and at the University Paul Sabatier
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Frank Hutter - Towards Deep Learning 2.0: Going to the Meta-Level

November 11, 2021 - Frank Hutter - Professor of Computer Science at the University of Freiburg
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Javier González Hernández - Causal Bayesian Optimisation

October 21, 2021 - Javier González Hernández - Microsoft Research, Cambridge
Details

Roberto Calandra - Bayesian Optimization for Robotics

October 14, 2021 - Roberto Calandra - Research Scientist at Facebook AI Research
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Emtiyaz Khan - Bayesian Principles for Learning-Machines

September 17, 2021 - Emtiyaz Khan - Team leader at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo
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Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning

September 2, 2021 - Ciara Pike-Burke - Lecturer in Statistics at Imperial College London
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José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning

July 15, 2021 - José Miguel Hernández Lobato - University Lecturer in Machine Learning at the Department of Engineering in the University of Cambridge, UK
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Carl Henrik Ek - Modulating surrogates for bayesian optimization

June 10, 2021 - Carl Henrik Ek - Senior Lecturer in the Computer Laboratory at the University of Cambridge, UK, and a Docent in Machine Learning at the Royal Institute of Technology, Sweden
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Peter Stone - Efficient Robot Skill Learning

May 13, 2021 - Peter Stone - Professor, University of Texas, Austin; Executive Director, Sony AI America
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Laurence Aitchison - Deep Kernel Processes

March 4, 2021 - Laurence Aitchison - Senior Lecturer, Computational Neuroscience Unit, University of Bristol
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Andrew G. Wilson - How do we build models that learn and generalize?

January 21, 2021 - Andrew G. Wilson - Assistant Professor, Courant Institute of Mathematical Sciences and Center for Data Science, New York University
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Vincent Adam - Sparse methods for markovian GPs

January 14, 2021 - Vincent Adam - Senior Machine Learning Researcher, Secondmind; Postdoctoral researcher, Aalto University
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M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it

December 17, 2020 - Matthew E. Taylor - Associate Professor, Department of Computing Science, Director at The Intelligence Robot Learning Laboratory, University of Alberta
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Arthur Guez - Value-driven Hindsight Modelling

November 19, 2020 - Arthur Guez - Google DeepMind
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Alexandra Gessner - Integration for and as Bayesian inference

November 12, 2020 - Alexandra Gessner - Ph.D. candidate, Probabilistic Numerics group, The Max Planck Institute for Intelligent Systems in Tübingen
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Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning

October 29, 2020 - Arno Solin - Assistant Professor in Machine Learning, Department of Computer Science, Aalto University
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Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind -

October 22, 2020 - Siddharth Reddy - Ph.D. candidate, Berkeley Artificial Intelligence Research Lab, University of California, Berkeley
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Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization

October 8, 2020 - Peter Frazier - Associate Professor of Operations & Information Engineering, Cornell University; Staff Data Scientist, Uber
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Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis

October 1, 2020 - Gabriel Dulac-Arnold - Researcher at Google Research
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Philipp Hennig - Computation under Uncertainty

September 24, 2020 - Philipp Hennig - Professor for the Methods of Machine Learning, University of Tuebingen; Adjunct scientist, Max Planck Institute for Intelligent Systems in Tuebingen
Details

Magnus Rattray - Non-parametric modelling of gene expression in time and space

September 10, 2020 - Magnus Rattray - Professor of Computational & Systems Biology, University of Manchester
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Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning

August 27, 2020 - Andreas Krause - Professor of Computer Science, Director of Learning & Adaptive Systems Group, ETH Zurich
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Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning

August 6, 2020 - Rahul Kidambi - Post-doctoral researcher, Department of Computer Science, Cornell University
Details

Arthur Gretton - Generalized Energy-Based Models

July 30, 2020 - Arthur Gretton - Professor, Gatsby Computational Neuroscience Unit, Director of the Centre for Computational Statistics and Machine Learning, University College London
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Gergely Neu - A unified view of entropy-regularized Markov decision processes

May 21, 2020 - Gergely Neu - Research Assistant Professor, AI group, DTIC, Universitat Pompeu Fabra
Details

Want to get involved?

If you have interesting research that you'd like to share, please get in touch.

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