NICE 2018 Agenda

 

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Tuesday, February 27th
Time
Topic
Speaker
8:00
Murat Okandan, NICE Workshop Foundation
8:10
Leading the Evolution of Compute
(watch presentation)
Mike Mayberry, Intel Corporation
8:30
Programmatic panel
(watch presentation)
Karlheinz Meier, EU HBP
Hava Siegelmann, DARPA
Kaushik Roy, SRC/C-BRIC
9:25
Spiking Neuron Implementations of Several Fundamental Machine Learning Algorithms
(watch presentation)
Craig Vineyard, Sandia National Laboratories
9:50
20 Minute Break
10:10
Keynote – The Deep Learning Revolution
(watch presentation)
(download pdf)
Terry Sejnowski, Salk Institute
10:55
On-Device Intelligence with Deep Random Projection Networks
(watch presentation)
Dhireesha Kudithipudi, RIT
3×10 Minute Lightning Talks
11:20
Bioinspired dynamic frontend for spike-based speech recognition
(watch presentation)
Jin-Ping Han, IBM
11:30
Towards Neuromorphic Complexity Analysis
(watch presentation)
(download ppt)
Johan Kwisthout, Radboud University
11:40
A neural-inspired software stack
(watch presentation)
Fred Rothganger, Sandia National Laboratories
11:45
Lunch
1:15
Designing processors for the nascency of machine intelligence
(watch presentation)
Simon Knowles, Graphcore
1:40
A Pulse-Gated Mechanism for Synaptic Copy Between Neural Circuits
(watch presentation)
(download pdf)
Andrew Sornborger, Los Alamos National Laboratory
2:05
Lifelong Learning in Machines
(watch presentation)
Hava Siegelmann, DARPA
2:30
45 Minute Poster & Demos Break
(poster intros)
(watch demos)
3:15
Sparse Embeddings of Spin-glass Spiking Neuron Networks on Neuromorphic Hardware for Community Identification Task
(watch presentation)
Kathleen Hamilton, Oak Ridge National Laboratory
New Architectures
Time
Topic
Speaker
3:40
Towards the Second Generation BrainScaleS System
(watch presentation)
Johannes Schemmel, Heidelberg University
4:05
SpiNNaker2 – Towards extremely efficient digital neuromorphics and multi-scale brain emulation
(watch presentation)
(download pdf)
Sebastian Hoppner, TU Dresden
4:30
Loihi Architecture Overview
(watch presentation)
(download pdf)
Mike Davies, Intel
4:45
Open mic & Discussion
(watch presentation)
6:00-8:00
Snacks and Drinks
Wednesday, February 28th
Time
Topic
Speaker
8:00
Welcome
Karlheinz Meier, University of Heidelberg
8:15
Some Observations About the Near Future of Alternative Computing Technology
(watch presentation)
(download ppt)
Bob Colwell
9:00
The Dynamic Link Architecture
(watch presentation)
Christoph von der Malsburg, Platonite
9:25
How Do Brains Learn about the Physical World
(watch presentation)
Garrett Kenyon, Los Alamos National Laboratory
9:50
30 Break
10:10
Neuromorphic Networks of Spiking Neurons Learn to Learn
(watch presentation)
(download pdf)
Wolfgang Maass, TU Graz
10:35
Ion channels, active dendrites, and computation
(watch presentation)
(download pdf)
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
(watch presentation)
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
(watch presentation)
Elliot J. Fuller, Sandia National Laboratories
11:55
Efficient Biosignal Processing with Brain-inspired High-dimensional Computing: A Universal ExG Classifier
(watch presentation)
(download pdf)
Abbas Rahimi, ETH Zurich
12:10
Lunch
1:15
Introducing CAL: Context Aware Learning
(watch presentation)
(download pdf)
Campbell Scott,
IBM
1:40
Working memory for structured data in neural networks
(watch presentation)
Fritz Sommer,
UC Berkeley
2:05
Brain-morphism: Astrocytes as Memory Units
(watch presentation)
(download pdf)
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
(watch presentation)
(download pdf)
Gangotree Chakma, University of Tennessee
4:05
Neural Algorithms for Scientific Computing
(watch presentation)
(download ppt)
Brad Aimone, Sandia National Laboratories
4:30
Open mic & Discussion
(watch presentation)
6:00
Transportation
6:30-8:00
Dinner Pumpkin Ridge Golf Course – 12930 NW Old Pumpkin Ridge Rd, North Plains, OR 97133, with Speaker George Dyson
Thursday, March 1st
Time
Topic
Speaker
8:00
Welcome
Brad Aimone, Sandia National Laboratories
8:15
Introducing Loihi, Intel’s neuromorphic research chip with integrated learning
(watch presentation)
(download pdf)
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
(watch presentation)
(download ppt)
Thomas Cleland, Cornell
9:50
30 Break
10:10
Building applications with next generation neuromorphic hardware
(watch presentation)
(download pdf)
Chris Eliasmith, University of Waterloo
10:35
Experiments on BrainScaleS
(watch presentation)
(download pdf)
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
(watch presentation)
(download pdf)
Konstantinos Michimizos, Rutgers University
11:10
Multi-Precision Deep Neural Networks
(watch presentation)
Sek Chai, SRI International
11:20
Biologically inspired memory enhancement of deep recurrent neural networks
(watch presentation)
(download pdf)
Xin Wang, Intel Corporation
11:30
From Analog to Digital and Back
(watch presentation)
(download pdf)
George Dyson
11:50
Lunch
1:15
Embedded Learning on Neuromorphic Systems: Towards a Unified Computing Framework
(watch presentation)
Emre Neftci, UC Irvine
1:40
Impacts of Quantization and Compression on Reinforcement Learning Policy Performance
(watch presentation)
(download ppt)
Sam Green, Sandia National Laboratories
2:05
Diverse Neurons and Inhomogeneous Neural Networks
(watch presentation)
(download ppt)
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
(watch presentation)
(download pdf)
William Severa, Sandia National Laboratories
3:40
Deep supervised learning using local errors
(watch presentation)
Hesham Mostafa, UC San Diego
4:05
X^3: A biologically inspired, high-speed algorithm for feature learning
(watch presentation)
(download pdf)
William Hahn, MPCR
4:30
Open mic & Discussion
5:15
Wrap up/Adjourn
(watch presentation)