Seminars

All talks take place on Thursdays at 13:00, unless otherwise stated.

Forthcoming Online Seminars



21 October 2021 – 14:00 BST (note unusual time)

Yaoda Xu, Psychology Department, Yale University, USA
Limited Correspondence in Visual Representation between the Human Brain and Convolutional Neural Networks

 


4 November 2021 – 15:00 GMT
Katherine Hermann, Department of Psychology, Stanford University, USA

TBC

 



2 December 2021

Kenneth Stanley, Department of Computer Science, The University of Central Florida, USA

TBC

 


POSTPONED – POSTPONED – New Date to be confirmed
Daniel Bear, Department of Psychology,  Stanford University, USA
Learning Graphical Representations of Scenes for Physical Understanding

 


Past Seminars


8 October 2021 – 15:00 BST
Kate Storrs, Justus Liebig University, Giessen, Germany
Understanding Mid-Level Vision through Unsupervised Learning

[Computational Neuroscience Unit/Mind and Machine joint Seminar]

Click here to join the meeting on Teams


7 October 2021 – 13:00 BST
Nikolaus Kriegeskorte, Zukerman Institute, Columbia University, USA
Controversial Stimuli: Optimizing Experiments to Adjudicate Among Computational Hypotheses


9 September 2021 (16:00 BST) – note unusual time
Philip J. Kellman, UCLA Human Perception Lab. University of California, Los Angeles, USA
Visual Perception of Shape


24 June 2021
Michael Herzog, Head of lab of Psychophysics at the Brain Mind Institute (BMI) at École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
About Fundamentals of Vision


10 June 2021
Rufin VanRullen, Research Director, CNRS, Centre de Recherche Cerveau et Cognition (CerCo), Toulouse, France
Do Deep Learning Latent Spaces Resemble Human Brain Representations?


27 May 2021 
Jean-Rémi King, CNRS Researcher, Department of Cognitive Science of École Normale Supérieure, Paris, France
Brains vs A.I: The Case of Language


Profile picture13 May 2021
Roland W. Fleming,  Kurt Koffka Professor of Experimental Psychology, Giessen University, Germany
Learning to See Stuff


22 April 2021 
Adam Kortylewski, Postgraduate Researcher, Johns Hopkins University, Baltimore, USA
Robust Computer Vision through Approximate-Analysis-by-Synthesis with Compositional Generative Networks


1st April 2021
Dylan Paiton, Institute for Theoretical Physics, University of Tübingen, Germany
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding


18 March 2021
Zhaoping Li, Head of Sensory and Sensorimotor Systems, Max Planck Institute for Biological Cybernetics, Germany
From V1SH to CPD : A New Framework for Understanding Vision


11 March 2021
Felix Hill, Senior Research Scientist at DeepMind, London, UK
A Developmental Pathway to Human-Like Intelligence in Machines


3rd December 2020 
Blake Richards, Learning in Neural Circuits Laboratory (Linc Lab), Mila and McGill University, Montreal, Canada
Learning from Unexpected Events in the Neocortical Microcircuit


5 November 2020 
Dileep George, Co-Founder of Vicarious AI, San Francisco, USA
Triangulating General Intelligence, Cognition, and Cortical Microcircuits


8 October 2020 
Felix Wichmann, Neural Information Processing, Tübingen, Germany
Object Recognition in Man and Machine


17 September 2020
Konrad Körding, University of Pennsylvania
An Optimization Based Way of Thinking About Brains


23 July 2020
Brenden Lake, Human & Machine Learning Lab and CILVR Lab  (New York, USA)
Compositional Generalization in Minds and Machines

 


2nd July 2020 
Tim Kietzmann, Donders Institute for Brain, Cognition and Behaviour (Radboud University, The Netherlands).
Deep Neural Networks as a Framework for Understanding the Dynamic Computations of the Human Visual System


11 June 2020 
Thomas Serre, Cognitive, Linguistic & Psychological Sciences Department, Carney Institute for Brain Science, Brown University, USA
Feedforward and Feedback Processes in Visual Recognition


28 May 2020
Adrien Doerig, Psychophysics Laboratory, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Crowding, Neural Networks and the Architecture of the Visual System


14 May 2020 
Guillermo Puebla, School of Psychological Science, University of Bristol, UK
Learning Programs from Rewards with Relational Reinforcement Learning

 


4 June 2020 – Postponed
Michael Herzog, Psychophysics Laboratory, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland


23 April 2020 – Postponed
Emmanuel Dupoux, École des Hautes Etudes en Sciences Sociales (EHESS) and Facebook AI Research.


16 April 2020 – Postponed
James V Stones (University of Sheffield, UK)
Are Neurons Efficient?


2 April 2020 – Postponed
Peter Flach (Computer Science,  University of Bristol, UK)


12 March 2020
Leonidas Doumas (School of Philosophy, Psychology and Language Sciences, Edinburgh, UK)
Cross-Domain Transfer in Humans and Machines


27 February 2020
Cian O’Donnell (Computational and Theoretical Neuroscience, Computer Science,  Bristol, UK)
Neural Circuit Redundancy, Stability, and Variability in Developmental Brain Disorders


20 February 2020
Jessica Hamrick (DeepMind, London, UK)
Mental Simulation, Imagination, and Model-Based Deep RL


12 December 2019
Nina Kazanina, School of Psychological Science, University of Bristol, UK
Language in the Mind and Machine

 


14 November 2019 
Chris Summerfield | Human Information Processing Lab, Experimental Psychology, Oxford University, UK
Neoconnectionism: Deep Learning Models of Cognitive Function


24 October 2019 
Charles Leek | Institute of Life and Human Sciences, School of Psychology, Liverpool, UK
What do Deep Neural Networks Tell us about Biological Vision?


10 October 2019
Dima Damen, Visual Information Lab, Computer Science, Bristol, UK
A Fine-grained Perspective onto Object Interactions

 


3 October 2019
Francis Song, DeepMind, London, UK
Deep Neural Networks Are Like The Brain, Except When They Aren’t

 


19 June 2019
Marco Baroni, Research Scientist at Facebook Artificial Intelligence (FAIR) Paris, and Catalan Institution for Research and Advanced Studies (ICREA) Barcelona
The Emergence of a Grammatical Subsystem in Neural Language Models
[Joint work with: Yair Lakretz, Dieuwke Hupkes, Theo Desbordes, Germán Kruszewski and Stan Dehaene]


6 June 2019
Ella Gale | Research Associate | Psychological Science | Bristol, UK
Adding Structural Awareness to Deep Neural Networks Using Clusterflow Allows us to Defeat Adversarial Images and Solve Relational Problems

 


23 May 2019
Bradley C. Love,  Prof of Cognitive and Decision Sciences, Experimental Psychology, UCL, UK
Levels of Representation in a Deep Learning Model of Categorisation


9 May 2019
Andrew Saxe, Postdoctoral Research Associate, Experimental Psychology, Oxford University, UK
A Mathematical Theory of Semantic Development in Deep Neural Networks


25 April 2019
Nathan Lepora, Tactile Robotics Research Group at  Bristol Robotics Laboratory, Department of Engineering Mathematics, University of Bristol, UK
Biomimetics and AI for Dexterous Robots


28 March 2019
Irina Higgins, Senior Research Scientist, Google DeepMind, London, UK
What is Disentangling and does Intelligence do it?

 


14 March 2019
Rui Ponte Costa, Computational Neuroscience and Machine Learning, Department of Computer Science, University of Bristol, UK
Powerful Learning via Cortical Microcircuits


28 February 2019
Conor Houghton,  Computer Science, University of Bristol, UK
A Kozachenko-Leonenko Estimator for Mutual Information on Metric Spaces

 


14 February 2019
Ryan Blything, Research Associate, Psychological Science, Bristol, UK
Generalisation in Visual Object Recognition: A Comparison of Performance in Humans and Neural Networks

 


31st January 2019
Robert M. French, Research Director, CNRS, Université de Bourgogne, France
Understanding the Dynamics of Analogy-Making: New Analytical Techniques from Eye-Tracking

 


17 January 2019
Jeff Mitchell, Senior Research Associate, Psychological Science, University of Bristol, UK
Generalisation in Natural Language Processing


6 December 2018
Colin Davis | Psychological Science | University of Bristol, UK
What is the Code that Readers Use to Represent Printed Words?

 


22 November 2018
Hans Op de Beeck | Group leader of Human Brain Imaging and Rodent Visual Cognition | Laboratory of Biological Psychology | KU Leuven | Belgium
The Human Visual System is not a General Purpose Object Recognition Machine: Evidence from Neuroimaging and Artificial Neural Networks


1st November 2018
Ella Gale | Research Associate | Psychological Science | University of Bristol, UK
Selectivity Metrics can Overestimate the Selectivity of Units: A Case Study on AlexNet

 


18 October 2018
Peter Battaglia | Senior Research Scientist | Google DeepMind | London, UK
Object-Oriented Intelligence

 


4 October 2018
Roland Baddeley |  Psychological Science | University of Bristol, UK
A Theory of How Deep Neural Networks Work Based on Symmetry and Non-commutative Bayesian Inference

 


27 September 2018
Alex Graves | Research Scientist | Google DeepMind | London, UK
Computing with Neural Networks

 


5 July 2018
Simon Stringer, Director | Theoretical Neuroscience and Artificial Intelligence Laboratory | Department of Experimental Psychology | University of Oxford, UK
Feature Binding within a Spiking Neural Network Model of the Primate Ventral Visual Pathway


14 June 2018
Ari Morcos | DeepMind | London, UK
Towards an Understanding of Representational Structure in Deep Neural Networks

 


18 May 2018
Simon Thorpe  | Director of the CerCo UMR 5549 (CNRS-UT3), France
Grandmother Cells and Spiking Neural Networks

 


16 May 2018
John E. Hummel | University of Illinois, USA
Different Algorithms for Associative and Relational Learning