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shlizee / NeuroAI

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NeuroAI-UW seminar, a regular weekly seminar for the UW community, organized by NeuroAI Shlizerman Lab.

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University of Washington NeuroAI Seminar

Welcome to NeuroAI-UW seminar, a regular weekly seminar for UW community organized by NeuroAI Shlizerman Lab.

Meetings are currently held virtually (Summer & Fall 2020, Winter, Spring & Fall 2021, Winter, Spring 2022). Contact us if you would like to join! UW students can enroll into designated courses: AMATH 500L or EE 598F to participate in the seminarial activities.

New: We will be positing some of the invited visitors talks in NeuroAI YouTube playlist.

2022 Spring Schedule

Thanks Ryan Vogt and Jingyuan Li for being the Student Organizers.

Date Paper/Activity Student Presenter
04/01/2022 Organizational & Intro Meeting
04/08/2022 VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning Kun Su, Mingfei Chen, Harsha Vardhan
The Causal-Neural Connection: Expressiveness, Learnability, and Inference Rahul Biswas, Shirui Chen, Xiulong Liu
04/15/2022 ILQR-VAE : Control-base Learning of Input Driven Dynamics with Application To Neural Data Pamel Kang, Trung Le, Jingyuan Li
Neural Active Learning with Performance Guarantees Zhuochun Liu, Zhongshu Meng, Jinlin Xiang
04/22/2022 Inferring Latent Dynamics Underlying Neural Population aCTIVITY VIA neural Differential Equations Michael Nolan, Saba H, Destiny Alvarado
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph Yang Zheng, Anoop Mysore Nataraja, Malek Itani
04/29/2022 Guest Speaker Kevin Xia (Columbia University)

05/06/2022 Towards Biologically Plausible Convolutional Networks Xiangyu Gao, Yujia Liu, Xinyue Sun
Deep Reinforcement Learning with Spiking Q-Learning Jingwei Xu, Miranda Anderson, Jimin Kim
05/13/2022 A3D3 Speakers
05/20/2022 TBA
05/27/2022 Guest Speaker Claudio Gentile (Google)

06/03/2022 A3D3 Speakers
06/10/2022 Guest Speaker Marine Schimel (Cambridge)

2022 Winter Schedule

Date Paper/Activity Student Presenter
01/14/2022 Organizational Meeting
01/21/2022 Where is all the nonlinearity: flexible nonlinear modeling of behaviorally relevant neural dynamics using recurrent neural networks Michael Nolan, Saba Heravi, Ryan Vogt, Zekun Chen
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity Kun Su, Xiangyu Gang, Pamel Kang, Jingyuan Li
01/28/2022 Neural Active Learning with Performance Guarantees Xiulong Liu, James Hazelden, Jinlin Xiang, Liem Vu
Dynamic Causal Modelling Revisited Rahul Biswas, Astitwa Sarthak Lathe, Trung Le
02/04/2022 A3D3 NeuroAI
OpenLabCluster Demo Jingyuan Li (UW ECE), Moishe Kesselman (UW CSE)
Detection of Sleep Spindles with FPGA Xiaohan Liu (UW ECE), Aidan Yokuda (UW ECE)
Somatotopic representation of texture sensation in the primary somatosensory and motor cortices of mice Megan Lipton (Purdue Neurobiology)
02/11/2022 Guest Speaker Eva L. Dyer (Gatech)

02/18/2022 Stabilizing Dynamical Systems via Policy Gradient Methods Jimin Kim, Mingfei Chen, Aidan Yokuda
AugMax: Adversarial Composition of Random Augmentations for Robust Training Yang Zheng, Xiaohan Liu, Yujia Liu, Xinyue Sun
02/25/2022 Guest Speaker Max Simchowitz (MIT)

03/04/2022 A3D3 NeuroAI
Optimizing brain stimulation using deep learning Seungbin Park (Purdue)
Quantifying the effect of stimulation protocols on rapid network connectivity inference Tomohiro Ouchi (UW)
Modeling Neural Population Activity with Spatiotemporal Transformer Trung Le (UW)
03/11/2022 Guest Speaker: Omid G. Sani (USC)

2021 Fall Schedule

Date Paper/Activity Student Presenter
10/08/2021 Organizational Meeting
10/15/2021 Representation learning for neural population activity with Neural Data Transformers Rahul Biswas, Jimin kim
Deep Reinforcement Learning for Neural Control Ryan Vogt, Jinlin Xiang
10/22/2021 A unified framework of online learning algorithms for training recurrent neural networks Harsha Vardhan, James Hazelden
Lyapunov-Guided Embedding for Hyper-parameter Selection in Recurrent Neural Networks Kun Su, Michael Nolan
10/29/2021 AL-SAR: Active Learning for Skeleton-based Action Recognition Xiulong Liu, Syed M. Aun Haider
How does it sound? Jingyuan Li, Trung Le
11/05/2021 Guest Speaker Xiulong liu (UW)

Guest Speaker Jingyuan Li (UW)

11/12/2021 Guest Speaker: Chethan Pandarinath (Georgia Tech)

Guest Speaker: Joel Ye (CMU)

11/19/2021 Local Plasticity rules can learn deep representations using self-supervised contrastive predictions Yang Zheng, Saba Heravi
AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ Xiangyu Gao, Yonghun Lee
11/26/2021 Thanksgiving Break
12/03/2021 Guest Speaker: Cristina Savin (NYU)

Guest Speaker: Owen Marschall (NYU)

2021 Spring Schedule

Date Paper/Activity Student Presenter
04/02/2021 Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking Chuanmudi Qin, Xiulong Liu, Kun Su
Backpropagation and the brain Ben Francis, Felix Tse, Trung Le
04/09/2021 Understanding self-supervised Learning Dynamics without Contrastive Pairs Jingyuan Li, Ayesha Ghaffar, Zidan Luo
Closed-Form Factorization of Latent Semantics in GANs Jingxi Yu, Xiangyu Gao, Yang Zheng
04/16/2021 Guest Speaker: Anqi Wu (Columbia University)

04/23/2021 Non-reversible Gaussian processes for identifying latent dynamical structure in neural data Rahul Biswas, Ryan Vogt, Michael Nolan
Modeling behaviorally relevant neural dynamics with a novel preferential subspace identification Saba Heravi, Astitwa Lathe, Yiren Wang, Jimin Kim
04/30/2021 Guest Speaker: Bolei Zhou (The Chinese University of Hong Kong)

05/07/2021 New Papers Discussion
05/14/2021 ICLR Paper Presentation
05/21/2021 No Meeting
05/28/2021 Guest Speaker: Omid G. Sani (USC)

06/04/2021 Guest Speaker: Yuandong Tian (Facebook)

2021 Winter Schedule

Date Paper/Activity Student Presenter
01/08/2021 Organizational Meeting
01/15/2021 Graph Convolutional Reinforcement Learning Jinlin Xiang, Trung Le
When Counterpoint Meets Chinese Folk Melody Haobo Zhang, Xiulong Liu, Kun Su
01/22/2021 Gradient Starvation: A Learning Proclivity in Neural Networks Ryan Vogt, Yang Zheng
Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function Michael Nolan, Ben Francis, Rahul Biswas
01/29/2021 Guest Speaker: Zhiyao Duan

02/05/2021 Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks Jingyuan Li, Saba Heravi, Yetao Chen
Improved protein structure prediction using potentials from deep learning Chris Yin, Jamie Park, Jimin Kim
02/12/2021 Unsupervised Sound Separation Using Mixture Invariant Training Kun Su, Jinlin Xiang, Zhichao Lei
Deep Reinforcement Learning and its neuroscientific implications Ben Francis, Trung Le, Saba Heravi
02/19/2021
02/26/2021 Guest Speaker: Kathryn Hess Bellwald

03/05/2021 Guest Speaker: Wenrui Zhang

03/12/2021 Guest Speaker: Mohammad Pezeshki

2020 Autumn Schedule

Date Paper/Activity Student Presenter
10/02/2020 Organizational Meeting
10/09/2020 Learning a Prior over Intent via Meta-Inverse Reinforcement Learning Yang Zheng, Rahul Biswas
Universality and Individuality in recurrent networks Michael Nolan, Ben Francis
10/16/2020 Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons Jinlin Xiang, Ryan Vogt
Low-dimensional dynamics for working memory and time encoding Jimin Kim, Trung Le, David Babin
10/23/2020 Guest Speaker: Niru Maheswaranathan

10/30/2020 Rotational Dynamics Reduce Interference Between Sensory and Memory Represenatations Jingyuan Li, Saba Heravi
Foley Music: Learning to Generate Music from Videos Kun Su, Xiulong Liu
11/06/2020 Guest Speaker: Christopher Cueva

11/13/2020 No meeting
11/20/2020 Guest Speaker: Alexandra Libby
11/27/2020 Thanksgiving Break - No meeting
12/4/2020 Guest Speaker: Irina Higgins

12/4/2020 Guest Speaker: Chuang Gan

12/11/2020 Research Video Updates

2020 Summer Schedule

We are reading papers published in recent Top AI Conferences (CVPR 2020, ICML 2020)!

Date Paper Keywords Presenter Presentation Link
7/30/2020 Improving the Gating Mechanism of Recurrent Neural Networks RNN Ryan Vogt Google Slides
Encoding Musical Style with Transformer Autoencoders Music Generation Kun Su Google Slides
8/6/2020 Controllable Orthogonalization in Training DNNs Network Optimization Yang Zheng Google Slides
Π´nets: Deep Polynomial Neural Networks Network Design Jinlin Xiang Google Slides
8/13/2020 Forecasting Sequential Data Using Consistent Koopman Autoencoders Time Series Prediction Saba Heravi Google Slides
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules RNN Jingyuan Li Google SLides
8/20/2020 Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition Graph, Skeleton Rahul Biswas Google Slides
Do RNN and LSTM have Long Memory RNN Jimin Kim Google Slides
8/27/2020 XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning Incremental Learning Kun Su Google Slides
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network RNN Saba Heravi Google Slides
9/3/2020 Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention RNN Ryan Vogt Google Slides
Deep Isometric Learning for Visual Recognition Network Design Jimin Google Slides
9/10/2020 Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation Weakly Supervised Jinlin Xiang Google Slides
Towards Global Explanations of Convolutional Neural Networks with Concept Attribution Interpretability Jingyuan Li Google Slides
9/17/2020 Low-rank Compression of Neural Nets: Learning the Rank of Each Layer Compression Rahul Biswas Google Slides
Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation Yang Zheng Google Slides
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