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<< June 2017 >>

Thursday, June 1, 2017

Monitoring Covert Visual Decisions via Neural Population Dynamics in Frontal Cortex

Seminar: Distinguished Lecture | June 1 | 4-5 p.m. | 489 Minor Hall

William T. Newsome, Vincent C.V. Woo Director of the Stanford Neurosciences Institute

Neuroscience Institute, Helen Wills

Wednesday, June 7, 2017

Cognitive Mapping and Planning for Visual Navigation

Seminar: Redwood Seminar | June 7 | 12-1:30 p.m. | 560 Evans Hall

Saurabh Gupta, UC Berkeley

Neuroscience Institute, Helen Wills

560 Evans
We introduce a novel neural architecture for navigation in novel environments that learns a cognitive map from first person viewpoints and plans a sequence of actions towards goals in the environment. The Cognitive Mapper and Planner (CMP) is based on two key ideas: a) a unified joint architecture for mapping and planning, such that the mapping is driven by the needs of the planner,...   More >

Friday, June 9, 2017

Sculpted Light in the Brain

Conference/Symposium: Neuroscience Seminar | June 9 | 8:30 a.m.-6 p.m. |  Stanley Hall

Bernardo Sabatini, Harvard Medical School; Hillel Adesnik, UC Berkeley; Josh Trachtenberg, UCLA; Laura Waller, UC Berkeley; Michael Hausser, University College London; Na Ji, UC Berkeley; Michael Lin, Stanford University; Rafael Yuste, Columbia University; Tommaso Fellin, Istituto Italiano di Tecnologia; Ehud Isacoff, UC Berkeley

Neuroscience Institute, Helen Wills

“Sculpted Light in the Brain” is a one-day conference and workshop aimed at fostering collaborations between neuroscientists, computer scientists, optics researchers, and other scientists who share the common interest of developing better technology to observe and control neural activity in the awake, behaving brain. “Sculpted Light” refers to a broad class of methods where light is shaped to...   More >

Wednesday, June 14, 2017

Computational experiments with two neuro-inspired abstractions: Hebbian learning and spike timing information

Seminar: Redwood Seminar | June 14 | 12-1:30 p.m. | 560 Evans Hall

Upamanyu Madhow, UCSB

Neuroscience Institute, Helen Wills

In this talk, we discuss early work on two different neuro-inspired computational abstractions. In the first, we investigate flavors of competitive Hebbian learning for bottom-up training of deep convolutional neural networks. The resulting sparse neural codes are competitive with layered autoencoders on standard image datasets. Unlike standard training based on optimizing a cost function, our...   More >

Monday, June 19, 2017

A Deeper Understating of Deep Learning - Why Deep Neural Networks work so well?

Seminar: Redwood Seminar | June 19 | 12-1:30 p.m. | 560 Evans Hall

Naftali Tishby, The Hebrew University of Jerusalem

Neuroscience Institute, Helen Wills

Through analytical and numerical studies of Deep Neural Networks (using standard TensorFlow) in the ""Information Plane"" - the Mutual Information the network layers preserve on the input and the output variables - we obtain the following new insights:

1. The training epochs, for each layer, are divided into two phases: (1) fitting the training data - increasing the mutual information on the...   More >