SCHEDULE
Morning session
​9:15-9:30
Introduction
​9:30-10:15
Dhruv Batra : Towards Transparent AI Systems that Explain
​10:15-10:30
Coffee break and poster session
​10:30-11:15
Marcel Van Gerven : What artificial neural networks tell us about human brain function
​11:15-11:45
Spotlight presentations
11:45 - 12:30
Pieter Roelfsema : Feedforward and recurrent processing in the visual system
​12:30-14:00
Lunch
Afternoon session
​14:00-14:30
Spotlight presentations
​14:30-15:15
Jitendra Malik : Embodied Cognition: Lessons from Ontogeny and Phylogeny
​15:15-15:30
Coffee break and poster session
​15:30-16:15
Abhinav Gupta : Self-supervised Learning: taking cues from babies
16:15-17:00
Nikolaus Kriegeskorte : Testing complex brain-computational models to understand how the brain works
17:00-17:45
Panel discussion(with the invited speakers) : TBA
17:45-18:00
Concluding remarks
Posters
1. Discovering Perceptual Attributes in a Deep Local Material Recognition Network
Gabriel Schwartz, Ko Nishino
2. Examining Representational Similarity in ConvNets and the Primate Visual Cortex
Abhimanyu Dubey, Jayadeva Jayadeva, Sumeet Agarwal
3. Shape Completion with Recurrent Memory
Xin Yang
4. A Biologically Motivated Software Retina for Robotic Vision Applications
Jan Paul Siebert, Adam Schmidt, Gerardo Aragon-Camarasa, Nick Hockings, Xiaomeng Wang, William Cockshott
5. Generative Adversarial Motion to Image Synthesis
Kumar K Agrawal, Arna Ghosh
6. The Variational Walk-Back Algorithm
Yoshua Bengio, Anirudh Goyal, Nan R Ke
7. Comparing the effects of scene segmentation on human and convolutional neural network performance
Max M. Losch*, Noor Seijdel*, H Steven Scholte
8. Event-based Backpropagation
Peter O'Connor, Max Welling