NICE 2018 Agenda




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Tuesday, February 27th
Time
Topic
Speaker
8:00
Welcome
8:10
Mike Mayberry, Intel Corporation
8:30
Programmatic panel
Karlheinz Meier, EU HBP
Hava Siegelmann, DARPA
Kaushik Roy, SRC/C-BRIC
9:25
Spiking Neuron Implementations of Several Fundamental Machine Learning Algorithms
Craig Vineyard, Sandia National Laboratories
9:50
20 Minute Break
10:10
Keynote – The Deep Learning Revolution
Terry Sejnowski, Salk Institute
10:55
Sparse Embeddings of Spin-glass Spiking Neuron Networks on Neuromorphic Hardware for Community Identification Task
Kathleen Hamilton, Oak Ridge National Laboratory
3×10 Minute Lightning Talks
11:20
Bioinspired dynamic frontend for spike-based speech recognition
Jin-Ping Han, IBM
11:30
Towards Neuromorphic Complexity Analysis
Johan Kwisthout, Radboud University
11:40
A neural-inspired software stack
Fred Rothganger, Sandia National Laboratories
11:45
Lunch
1:15
Simon Knowles, Graphcore
1:40
A Pulse-Gated Mechanism for Synaptic Copy Between Neural Circuits
Andrew Sornborger, Los Alamos National Laboratory
2:05
Lifelong Learning in Machines
Hava Siegelmann, DARPA
2:30
45 Minute Poster & Demos Break
New Architectures
Time
Topic
Speaker
3:15
Embedded Learning on Neuromorphic Systems: Towards a Unified Computing Framework
Emre Neftci, UC Irvine
3:40
Towards the Second Generation BrainScaleS System
Johannes Schemmel, Heidelberg University
4:05
SpiNNaker2 – Towards extremely efficient digital neuromorphics and multi-scale brain emulation
Sebastian Hoppner, TU Dresden
4:30
Loihi Architecture Overview
Mike Davies, Intel
4:45
Open mic & Discussion
6:00-8:00
Snacks and Drinks
Wednesday, February 28th
Time
Topic
Speaker
8:00
Welcome
8:15
Bob Colwell
9:00
Christoph von der Malsburg, Platonite
9:25
How Do Brains Learn about the Physical World
Garrett Kenyon, Los Alamos National Laboratory
9:50
30 Break
10:10
Neuromorphic Networks of Spiking Neurons Learn to Learn
Wolfgang Maass, TU Graz
10:35
Weinan Sun, Janelia Farm
11:00
Adrienne Fairhall, University of Washington
4×10 Minute Lightning Talks
11:25
NeuADC: Neural Network Inspired Architecture to Exploit Learning for Analog-to-Digital Conversion
Xuan Zhang, Washington University
11:35
Quasi CNN
Bill Aronson, AI Research Group
11:45
A novel three-terminal memory with ultra-low energy and superior analog behavior
Elliot J. Fuller, Sandia National Laboratories
11:55
Efficient Biosignal Processing with Brain-inspired High-dimensional Computing: A Universal ExG Classifier
Abbas Rahimi, ETH Zurich
12:10
Lunch
1:15
Introducing CAL: Context Aware Learning
Campbell Scott,
IBM
1:40
Fritz Sommer,
UC Berkeley
2:05
Brain-morphism: Astrocytes as Memory Units
Konstantinos Michmizos, Rutgers University
2:30
45 Minute Poster & Demos Break
Scientific Computing
Time
Topic
Speaker
3:15
Rick Stevens, Argonne National Laboratory
3:40
Training Neuromorphic Systems for Scientific Applications
Gangotree Chakma, University of Tennessee
4:05
Neural Algorithms for Scientific Computing
Brad Aimone, Sandia National Laboratories
4:30
Open mic & Discussion
6:00
Transportation
6:30-8:00
Dinner (Speaker: George Dyson)
Thursday, March 1st
Time
Topic
Speaker
8:00
Welcome
8:15
Introducing Loihi, Intel’s neuromorphic research chip with integrated learning
Mike Davies, Intel Corporation
9:00
Continuous learning and catastrophic forgetting – what can we learn from the brain?
Maxim Bazhenov, UC San Diego
9:25
Neuromorphic algorithms derived from biological olfaction
Thomas Cleland, Cornell
9:50
30 Break
10:10
On-Device Intelligence with Deep Random Projection Networks
Dhireesha Kudithipudi, RIT
10:35
Experiments on BrainScaleS
Sebastian Schmitt, Heidelberg University
4×10 Minute Lightning Talks
11:00
Gridbot: A Spiking Neural Network Model of the Brain’s Navigation System for Autonomous Robots
Konstantinos Michimizos, Rutgers University
11:10
Multi-Precision Deep Neural Networks
Sek Chai, SRI International
11:20
TBA
TBA
11:30
TBA
11:45
Lunch
1:15
Building applications with next generation neuromorphic hardware
Chris Eliasmith, University of Waterloo
1:40
Impacts of Quantization and Compression on Reinforcement Learning Policy Performance
Sam Green, Sandia National Laboratories
2:05
Diverse Neurons and Inhomogeneous Neural Networks
Albert Lee, UCLA
2:30
45 Minute Poster & Demos Break
Neuromorphic Computing
Time
Topic
Speaker
3:15
Whetstone: An accessible, platform-independent method for training spiking deep neural networks for neuromorphic processors
William Severa, Sandia National Laboratories
3:40
Deep supervised learning using local errors
Hesham Mostafa, UC San Diego
4:05
X^3: A biologically inspired, high-speed algorithm for feature learning
William Hahn, MPCR
4:30
Open mic & Discussion
5:15
Wrap up/Adjourn