March 20, 2019 - 4:00 pm
Demis Hassabis, Co-Founder & CEO, DeepMind
This talk is co-hosted by the Center for Brains, Minds, and Machines (CBMM) and MIT Quest for Intelligence.
Abstract: Demis Hassabis will discuss the capabilities and power of self-learning systems. He will illustrate this with reference to some of DeepMind's recent breakthroughs, and talk about...
Abstract: Demis Hassabis will discuss the capabilities and power of self-learning systems. He will illustrate this with reference to some of DeepMind's recent breakthroughs, and talk about...
March 19, 2019 - 4:30 pm
Dr. Amnon Shashua, President and CEO Mobileye, an Intel company; Senior Vice President, Intel Corporation;...
Please note change of location - this talk will be held in MIT 10-250.
This talk is co-hosted by the Center for Brains, Minds, and Machines (CBMM) and MIT Quest for Intelligence.
Speaker Biography: Professor Amnon Shashua is senior vice president at Intel Corporation and president and chief...
This talk is co-hosted by the Center for Brains, Minds, and Machines (CBMM) and MIT Quest for Intelligence.
Speaker Biography: Professor Amnon Shashua is senior vice president at Intel Corporation and president and chief...
November 30, 2018 - 4:00 pm
Singleton Auditorium(46-3002)
Ari Rosenberg, University of Wisconsin - Madison
Abstract: Our sensory systems are unable to directly sense all the aspects of the world we perceive. For example, our perception of the world as three-dimensional (3D) is compelling, but our eyes only detect two-dimensional (2D) projections of our surroundings. Creating accurate and precise 3D...
October 26, 2018 - 4:00 pm
Henry Evrard , Head of Research Group
CIN Functional and Comparative Neuroanatomy, Werner Reichardt Center...
Abstract: Interoception substantiate embodied feelings and shape cognitive processes including perceptual awareness. My lab combines architectonics, tract-tracing, electrophysiology, direct electrical stimulation fMRI (DES-fMRI), neural event triggered fMRI (NET-fMRI) and optogenetics in the...
October 19, 2018 - 4:00 pm
Prof. Daniel J. Kersten, University of Minnesota
Abstract: The existence of feedforward and feedback neural connections between areas in the primate visual cortical hierarchy is well known. While there is a general consensus for how feedforward connections support the sequential stages of visual processing for tasks such as object recognition,...
October 12, 2018 - 4:00 pm
Prof. Samory Kpotufe, Princeton University
Abstract: Estimating the mode or modal-sets (i.e. extrema points or surfaces) of an unknown density from sample is a basic problem in data analysis. Such estimation is relevant to other problems such as clustering, outlier detection, or can simply serve to identify low-dimensional structures in...
September 21, 2018 - 4:00 pm
Eric Shea-Brown, University of Washington
Abstract: There is an avalanche of new data on the brain’s activity, revealing the collective dynamics of vast numbers of neurons. In principle, these collective dynamics can be of almost arbitrarily high dimension, with many independent degrees of freedom — and this may reflect...
July 24, 2018 - 11:00 am
Dr. Joseph T. Lizier, The University of Sydney
Abstract:
The space-time dynamics of interactions in neural systems are often described using terminology of information processing, or computation, in particular with reference to information being stored, transferred and modified in these systems. In this talk, we describe an information-...
The space-time dynamics of interactions in neural systems are often described using terminology of information processing, or computation, in particular with reference to information being stored, transferred and modified in these systems. In this talk, we describe an information-...
July 2, 2018 - 4:00 pm
Prof. Lior Wolf, Tel Aviv University and Facebook AI Research
Abstract: Generative models are constantly improving, thanks to recent contributions in adversarial training, unsupervised learning, and autoregressive models. In this talk, I will describe new generative models in computer vision, voice synthesis, and music.
In music – I will...
In music – I will...
May 21, 2018 - 4:00 pm
Jonathan Miller, Associate Professor | Physics and Biology Unit, Okinawa Institute of Science and Technology...
Abstract: By a quirk of evolution, camouflaging octopus and cuttlefish report their visual perceptions by modulating their skin color and 3-d texture on time scales of seconds or minutes to match their surroundings (they are generative image modelers). Their survival demands that predators...
May 4, 2018 - 2:00 pm
Jon Shlens, Google Brain
Abstract:
Recent advances in machine learning have profoundly influenced our study of computer vision. Successes in this field have demonstrated the expressive power of learning representations directly from visual imagery — both in terms of practical utility and unexpected expressive abilities. In...
Recent advances in machine learning have profoundly influenced our study of computer vision. Successes in this field have demonstrated the expressive power of learning representations directly from visual imagery — both in terms of practical utility and unexpected expressive abilities. In...
April 20, 2018 - 4:00 pm
Phil Nelson, Google Research | Google Accelerated Science team
Abstract: Google Accelerated Sciences is a translational research team that brings Google's technological expertise to the scientific community. Recent advances in machine learning have delivered incredible results in consumer applications (e.g. photo recognition, language translation), and is now...
April 18, 2018 - 2:00 pm
Mikhail Belkin, Ohio State University
Abstract:
A striking feature of modern supervised machine learning is its pervasive over-parametrization. Deep networks contain millions of parameters, often exceeding the number of data points by orders of magnitude. These networks are trained to nearly interpolate the data by driving the training...
A striking feature of modern supervised machine learning is its pervasive over-parametrization. Deep networks contain millions of parameters, often exceeding the number of data points by orders of magnitude. These networks are trained to nearly interpolate the data by driving the training...
April 13, 2018 - 4:30 pm
Christof Koch, CBMM EAC member, Allen Institute for Brain Science
Abstract:
Rapid advances in convolutional networks and other machine learning techniques, in combination with large data bases and the relentless hardware advances due to Moore’s Law, have brought us closer to the day when we will be able to have extended conversations with programmable systems,...
Rapid advances in convolutional networks and other machine learning techniques, in combination with large data bases and the relentless hardware advances due to Moore’s Law, have brought us closer to the day when we will be able to have extended conversations with programmable systems,...
April 12, 2018 - 4:30 pm
Marge Livingstone, CBMM, Harvard Medical
Host: Tomaso Poggio
This talk is open to the CBMM Community only
This talk is open to the CBMM Community only