Reading Club

Discussion of machine learning, its applications, and related ideas

A brown-bag (bring your own lunch) reading club at TReNDs Center held mainly for cross pollination of ideas and “out of the comfort zone” fun. We read and discuss papers, tutorials, or packs of papers and ideas at once. The topics span all areas of machine learning, with a focus on Deep Learning, but also venture into brain imaging and theories of how the brain works. The goal is to both learn and refine the knowledge of important foundational concepts and stay current with the literature.

Email Sergey Plis at splis@gsu.edu if you want to be added to the club’s Slack. If you’re already a part of the TReNDS Center, join the #reading_group channel on our Slack workspace.

A list of topics with associated materials can be found on our GitHub page.


Upcoming Meetings

Spring 2024

04/19/24 – Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI

04/26/24 – On WebGPU

05/03/24 – Identifiability of nonlinear generative models


Past Meetings

Spring 2024

04/12/24 – Evaluation framework for interpretability methods Quantus (meta-Quantus) – (slides)(video) – Mahfuz presents

04/05/24 – Integrating Large Language Models (LLMs) with knowledge graphs – (slides)(video) – Mrinal presents

03/29/24 – How to guess a gradient – (slides)(video) – Pavel presents

03/22/24 – Emerging Trends in Fast MRI Using Deep-Learning Reconstruction on Undersampled k-Space Data: A Systematic Review – (slides)(video) – Brad presents

03/15/24 – Extensive childhood experience with Pokémon suggests eccentricity drives organization of visual cortex – (slides)(video) – Jordan presents

03/08/24 – A U-turn on Double Descent – (slides)(video) – Sergey presents

03/01/24 – Are Transformers Effective for Time Series Forecasting – (slides)(video) – Joanne presents

02/23/24 – A graph neural network framework for causal inference in brain networks – (slides)(video) – William presents

02/09/24 – Big Self-Supervised Models are Strong Semi-Supervised Learners – (slides)(video) – Minoo presents

02/02/24 – Genotype and Phenotype Differences in CADASIL from an Asian Perspective – (slides)(video) – Jordan presents

01/26/24 – Progress measures for grokking via mechanistic interpretability – (slides)(video) – Sergey presents

01/19/24 – Longitudinal Modelling of Disease Progression – (slides) – Alex presents

01/12/24 – Community-Aware Transformer for Autism Prediction in fMRI Connectome – (slides)(video) – Joanne presents

Fall 2023

12/08/23 – Best Papers of 2023 – (slides)(video)

11/03/23 – Causal Algorithms Tutorial – (demo)(slides)(video) – Kseniya presents

10/27/23 – Voyager: GPT-4 Agents in Minecraft – (slides)(video) – Mike and Mateo present

10/20/23 – From sparse to soft Mixture of Experts – (slides)(video) – Riyasat presents

10/13/23 –  Conditional Positional encodings for Vision Transformers – (slides)(video) – William presents

10/06/23 – Gradients without Backpropagation – (slides)(video) – Pavel presents

09/29/23 – Estimating Training Data Influence by Tracing Gradient Descent (slides)(video) – Mahfuz presents

09/22/23 – Contrastive Learning Inverts the Data Generating Process (slides)(video) – Yaorong presents

09/15/23 – Sparks of Plant Consciousness (slides)(video) – TJ presents

09/08/23 – ML-Ops in the cloud and beyond – (demo)(slides)(video) – Pratyush and Girish present

09/01/23 – Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles – (slides)(video) – Joanne presents

08/25/23 – Self-training with Noisy Student improves ImageNet classification – (slides)(video) – Minoo presents

Summer 2023

08/18/23 – Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining – (slides) (video) – Mrinal presents

08/11/23 – Learning to Exploit Temporal Structure for Biomedical Vision Language Processing – (slides) (video) – Zafar presents

07/28/23 – A somatic-cognitive action network alternates with effector regions in motor cortex – (slides) (notes) (video) – TJ presents

07/14/2023 – High Performance Compiler-Based Automatic Differentiation – (slides) (video) – Ludger presents (external speaker)

07/07/2023 – A Review on Multimodal Data Fusion Approaches (paper 1) (paper 2) (paper 3) – (video) (slides) Ibrahim presents

06/30/2023 – AI Institute June 2023 Workshop Discussion – (slides) Kseniya, Vaibhavi, and Pavel present

06/23/2023 – Label Propagation for Deep Semi-Supervised Learning (video) (slides) – Minoo presents

05/31/2023 – An Approach to Automatically Label & Order Brain Activity/Component Maps (video) (slides) – Joanne presents

05/26/2023 – Pointersect: Neural Rendering with Cloud Ray Intersection (video) (slides) – Mrinal presents

05/19/2023 – Efficiently Modeling Long Sequences with Structured State Spaces (video) (slides) – Eloy presents

05/12/2023 – Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention – (video) (slides) Sajad presents

05/05/2023 – Neural Collapse: A Review on Modelling Principles and Generalization (video) (slides) – Brad presents

Spring 2023

04/28/2023 – Causal Machine Learning for Healthcare and Precision Medicine (video) (slides) – Ibrahim presents

04/14/2023 – Toy Models of Superposition Continued (video) (slides) – Pavel presents

04/07/2023 – Singular Values For ReLU Layers (video) (slides) – Brad presents

03/31/2023 – On Causal and Anticausal Learning (video) (slides) – Sergey presents

03/24/2023 – Parameter Space Saliency Maps for Explainability (video) (slides) – Mahfuz presents

03/17/2023 – Unsupervised Deep Learning for Bayesian Brain MRI Segmentation (video) (slides) – William presents

03/10/2023 – Fixed Point Iterations in Deep Learning (video) – Mrinal presents

03/03/2023 – ChatGPT (video) (slides) – TJ presents

02/24/2023 – Towards Real-Time Object Detection With Region Proposal Networks (video) (slides) – Minoo presents

02/17/2023 – Galactica: A Large Language Model for Science (video) (slides) – Alexandre presents

02/10/2023 – Unfolding Argument: Why IIT and other causal structure theories cannot explain consciousness (video) (slides) – Kseniya presents

02/03/2023 – Superposition Memorization And Double Descent (video) (slides) – Eloy presents

01/27/2023 – Quantum Optimization – (video) (slides) – Anton presents

01/20/2023 – Non-Linear ICA (video) (slides) – Yaorong presents

01/13/2023 – Topology Preserving Deep Image Segmentation (video) – Noah presents

Fall 2022

11/18/2022 – Neural Race Reduction (video) (slides) – Brad presents

11/11/2022 – Improving Multimodal Fusion (video) (slides) – Ibrahim presents

11/08/2022 – Causal Learning Freeform Discussion (video) – David presents

10/28/2022 – AI & Art (video) (slides) – Farfalla presents

10/21/2022 – Multiplexed Immunofluorescence Imaging (video) (slides) – Mohamed presents

10/12/2022 – Quantum Machine Learning (video) (slides) – Pavel presents

10/07/2022 – Mixed Effect Spectral Vector Autoregressive Model (video) (slides) – Anastasia presents

09/30/2022 – Point Cloud Surface Reconstruction (video) (slides) – William presents

09/16/2022 – GATO (video) (slides) – TJ presents

09/09/2022 – Conformal Predictions (video) (slides) – Sergey presents

09/02/2022 – Monks and EEG – Kseniya presents

Summer 2022

08/26/2022 – Introspection with Influence Functions (video) – Noah presents

08/19/2022 – Label Propagation (paper 1) (paper 2) (video) (slides) – Minoo presents

08/05/2022 – ICML (& IJCNN) Highlights (video) (slides) – Alex, Mahfuz, and Sergey present

07/29/2022 – Deep Reinforcement Learning (video) (slides) – Eloy presents

07/22/2022 – Symmetry-Based Representations (video) – Eloy presents

07/15/2022 – Planning Meeting

07/08/2022 – Cortical Surface Generation (part 2) (video) (cortical++) (pialnn) (cortexode) – William presents

06/30/2022 – OHBM Recap (slides) – Group presents

06/17/2022 – Text-to-Image Generation (video) (slides) – TJ presents

06/10/2022 – Conformal PredictionSergey presents

06/03/2022 – Cortical Surface Generation Models (part 1) (video) (topofit) (deepcsr) (vox2cortex) – William presents

05/27/2022 – Dynamics in Shallow AutoEncoders (video) (slides)Brad presents

05/20/2022 – Theories of Consciousness (video) (slides)TJ presents

Spring 2022

04/29/2022 –Learning in High Dimensions Amounts to Extrapolation (video)Sergey presents

04/23/2022 – GSU Demo Day

04/15/2022 – 1000 Brains Theory (slides) (video)Eloy presents

04/08/2022 – Backprop and Neuroscience (slides) (video)Brad presents

04/01/2022 – Recurrent Independent MechanismsSergey presents

03/25/2022 – Topology Layer for Machine Learning (video) Noah presents

03/18/2022 – Multimodal Few-Shot Learning (slides) (video)Mrinal presents

03/11/2022 – Supervised Contrastive Learning (slides) (video)Mahfuz presents

03/04/2022 – Time Series Forecasting (slides) (video)Usman presents

02/25/2022 – Deep Learning in the Browser (slides) (video) Mohamed presents

02/18/2022 – Alpha Fold (slides) (video)TJ presents

02/11/2022 – Recurrent Models for Neuroimaging (video) (slides)Yaorong presents

02/04/2022 – If deep learning is the answer what is the question? (video) (slides)Brad presents

01/28/2022 – Cortical Flow (video) (slides)William presents

01/21/2022 – Best Ideas of 2021 (video) (slides)Group presentation

01/14/2022 – Multi Modal Deep Learning for Brain Development and Cognition(video) (slides)Yu-Ping presents

Fall 2021

12/17/2021 – Underspecification Challenges in Modern Machine LearningAlex presents

12/10/2021 – The physics of higher-order interactions in complex systems (video) (slides)Ashkan presents

12/03/2021 – Answer Set Programming (video) (slides)Sajad presents

11/19/2021 – Upside-Down Reinforcement Learning (video) (slides)TJ presents

11/12/2021 – Perspective on General AI (video)Sergey presents

11/05/2021 – Mixed Integer Programming (video)William presents

10/29/2021 – Multi-Task Self-Training (video) (slides)Eloy and Noah present

10/22/2021 – Fit Without Fear (video)Sergey presents

10/15/2021 – GPT-Codex (video) (slides)Mrinal presents

10/08/2021 – MLP Mixers (video) (slides)Alex presents

10/01/2021 – Dynamic Causal Models (video) (slides)Jack presents

09/24/2021 – Denoising Diffusion Probabilistic Models (video) (slides)Eloy presents

09/17/2021 – Causation and Discovery: Concepts, methods, and applications (video) (slides)David Danks presents (external speaker)

09/10/2021 – Symbolic Methods using Gradients for Neural Model Explanation (video) (slides)Mahfuz presents

09/03/2021 – Causal Representation Learning (video)Sergey presents

Summer 2021

08/20/2021 – Learning Function Structure in Neuromorphic Networks (video) (slides) – Amrit presents

08/13/2021 – Meshed-Memory Transformer (video) (slides)William presents

08/06/2021 – Generative Vision model for Breaking Captcha (video) (slides)Harsha presents

07/23/2021 – VAEs and Non-Linear ICA (video – part 1) (video – part 2) (slides)Rogers presents

07/16/2021 – Reinforcement Learning (pt 2) (video) (slides)TJ presents

07/09/2021 – Reinforcement Learning (pt 1) (video) (slides)TJ presents

06/25/2021 – PixelCNN (video)Will presents

06/18/2021 – How Neural Networks Extrapolate (video)Kevin presents

06/04/2021 – Normalizing Flows (NICE) (NVP) (MADE) (video) (slides)Eloy presents

05/28/2021 – Directed Functional Connectivity (video) (slides)Thomas presents

05/21/2021 – Neural Turing Machines (video) (slides)Eloy and Will present

05/14/2021 – Mythos of Model InterpretabilitySergey presents

05/07/2021 – Multi-Dimensional LSTMs (video) (slides) Yaorong presents

Spring 2021

04/30/2021 – Energy Based Out of Distribution Detection (video) (slides) – Kevin presents

04/23/2021 – Every Model is a Kernel Machine (video)Sergey presents

04/16/2021 – Neural Relational Inference for Interacting Systems (slides) (video)Usman presents

04/09/2021 – Transformers with Feedback Memory (slides) (video)Alex presents

04/02/2021 – Debugging Tests for Model Explanations (slides) (video) – Mahfuz presents

03/26/2021 – Hopfield Networks ARE all you need (slides) (video)Noah Presents

03/19/2021 – Single-shot Network Pruning (slides) (video)Riyasat and Noah present

03/12/2021 – “Brain, Language & Deep Learning” – Harsh presents

03/05/2021 – GIN-LiNGAM (slides) (video)Sajad presents

2/26/2021 – Geometric Deep Learning (video)Will presents

2/19/2021 – Intro to Causal Discovery (slides) (video)Sergey presents

2/12/2021 – PowerSGD (slides) (video)Brad presents

2/5/2021 – Dall-E (slides) (video) Eloy presents

1/22/2021 – Multiplicative Interactions and Where to Find Them (slides) (video)Alex presents

1/15/2021 – Siamese Networks and Self-Supervised Learning (slides) (video)Eloy and Alex present

Fall 2020

12/11/2020 – Notable Work at NeurIPS 202 (slides) (video)All present

12/04/2020 – Intelligence w/o Representation (slides) (video)Eloy presents

11/20/2020 – Stacked Capsule Autoencoders (slides) (video) Will presents

11/13/2020 – Learning Bifurcations (slides) (video)Jack presents

11/06/2020 – Curriculum by Smoothing (slides) (video)Alex presents

10/09/2020 – Transformers for Image Recognition (slides) (video) Eloy presents

10/02/2020 – Overfitting in Classification (slides)Thomas presents

09/25/2020 – Neural State MachinesJack presents

09/18/2020 – Hierarchial LSTMs/ Adversarial LSTMsWilliam presents

09/11/2020 – MRI Segmentation (second paper) (slides) Zafar Presents

09/04/2020 – World Models (slides) (video)Eloy presents

8/28/2020 – Deep Learning for Right Reasons (video) (slides)Noah presents

08/21/2020 – Sparsity Inducing Regularization (video)Riyasat presents

Summer 2020

08/14/2020 – Inference of Causal Relations in Dynamical Systems
(Taken Theorem video) Jack presents

08/07/2020 – Analytic Marching (slides) (video)William presents

07/31/2020 – Learning Graph Representations

07/24/2020 – CNNs on Graphs (video) Alex presents

07/10/2020 – Hierarchical LSTMs (video)William presents

06/26/2020 – ANIL (slides) (video)Alex presents

06/19/2020 – “Multitask Learning over graphs” (slides) (video) – Riyasat and Brad Present

06/12/2020 – MAML and iMAMLAlex presents

06/05/2020 – Contrastive Predictive CodingMahfuz presents

Spring 2020

05/29/2020 – Cutting out the Middle-Man:L Training and Evaluating Energy-Based Models without SamplingAlex presents

05/22/2020 – Energy-Based Models VideoJack and Alex present

05/15/2020 – Noise Contrastive EstimationSergey presents

05/08/2020 – “Representation Learning”Alex presents

05/01/2020 – ” Shortcut Learning in Deep Neural Networks”Alex presents

04/24/2020 – Fixed Point Layers (pt 2) – presented by Sergey

04/17/2020 – Fixed Point Layers – presented by Sergey

04/10/2020 – Multitask Learning – presented by Alex

03/13/2020 – A tutorial on Automatic Differentiation – presented by Sergey

03/06/2020 – Sanity Checks for Saliency Maps

02/28/2020 – Complexity control by gradient descent in deep networks

02/21/2020 – A mathematical theory of semantic development in deep neural networks

02/14/2020 – N/A

02/07/2020 – Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

01/31/2020 – Data-driven discovery of coordinates andgoverning equations

01/24/2020 – Neural Networks in System Identification

01/17/2020 – A tutorial on hidden Markov models and selected applications in speech recognition

Fall 2019

12/06/2019 – Meta-learning for neuroimaging

11/22/2019 – Nonlinear Dimensionality Reduction methods and a generalization

11/08/2019 – Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

11/01/2019 – Synthesizing Programs for Images using Reinforced Adversarial Learning

10/25/2019 – Introduction to Deep Q-Network

10/18/2019 – Hidden stratification

10/11/2019 – Neural Ordinary Differential Equations

10/04/2019 – Model Utility

09/27/2019 – Wasserstein GANs and other easier to train models

09/20/2019 – Generative Adversarial Networks (Intro)

09/13/2019 – Predictive coding theory of the mind: part II

09/06/2019 – Predictive coding theory of the mind: Intro

08/30/2019 – Confidence and accuracy: On Calibration of Modern Neural Networks

08/23/2019 – Deep learning model introspection

Summer 2019

08/16/2019 – Deep learning trends from the deep learning summer school

08/09/2019 – Variational Autoencoders: part II

08/02/2019 – Variational Autoencoders: part I

07/26/2019 – Attention in deep learning models: part II

07/19/2019 – Attention in deep learning models: part I

07/12/2019 – NLP successes of 2018: transfer learning


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