Binxu
  • Bio
  • Papers
  • Talks
  • Experience
  • Teaching
  • Writings
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  • Recent & Upcoming Talks
    • Computer Vision and Pattern Recognition Conference (CVPR 2026) — Tutorial
    • University of Missouri-Columbia — Geometry & Topology Seminar
    • University of Texas at Austin — Xuexin Wei Lab Meeting
    • Harvard University — Neuro120 Introduction to Computational Neuroscience
    • Flatiron Institute / CUNY — M.S. in Cognitive Science Special Seminar
    • University of Chicago — NeuroML Workshop
    • University of Minnesota — Department of Neuroscience Special Seminar
    • University of Cincinnati — Department of Biological Sciences Special Seminar
    • Janelia Research Campus — Computation and Theory Group Leader Special Symposium
    • Peking University (Shenzhen) — 1st International Young Scholars Forum, School of AI for Science
    • University of Oregon, Knight Campus — Department of Bioengineering Special Symposium
    • University of Wisconsin–Madison — Department of Psychology Special Seminar
    • Janelia Research Campus — Junior Scientist Workshop on Theoretical Neuroscience
    • SfN 2025 Nanosymposium
    • Renormalization for AI Safety Workshop — Invited Talk
    • Boston Diffusion Day — Invited Talk
    • Cold Spring Harbor Laboratory — NeuroAI Seminar
    • Poster at NEMI 2025 Workshop on Circuit underlying relational object generation in DiT
    • IAIFI Summer Workshop Talk
    • Talk at VSS2025 Session: Theory - Artificial neural networks
    • Talk at VSS2025 Symposium Model-optimized stimuli: more than just pretty pictures
    • Spring into Science Retreat Talk
    • Special Seminar at Washington University Neuroscience Department
    • Yale Cognitive & Neural Computation Lab Talk
    • SfN 2024 Nanosymposium
    • NAISYS2024 Conference Talk
    • KITP Deep Learning Program
    • SfN 2023 Nanosymposium
    • PhD Thesis Defense
    • Kempner Institute Invited Lecture
  • Publications
    • Circuit Mechanisms for Spatial Relation Generation in Diffusion Transformers
    • Where the Score Lives: A Wavelet View of Diffusion
    • Differentiable Faithfulness Alignment for Cross-Model Circuit Transfer
    • Matching Accuracy, Different Geometry: Evolution Strategies vs GRPO in LLM Post-training
    • Neuronal Tuning Aligns Dynamically with Object- and Texture Manifolds across the Visual Hierarchy
    • When Rule Learning Breaks: Diffusion Fails to Learn Parity of Many Bits
    • Feature accentuation along the encoding axes of IT neurons uncovers hidden differences in model-brain alignment
    • An analytical theory of power law spectral bias in the learning dynamics of diffusion models
    • A Random Matrix Perspective on the Consistency of Diffusion Models
    • Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
    • Into the Rabbit Hull: From Task-Relevant Concepts in DINO to Minkowski Geometry
    • The Unreasonable Effectiveness of Gaussian Score Approximation for Diffusion Models and its Applications
    • Diverse capability and scaling of diffusion and auto-regressive models when learning abstract rules
    • Do diffusion models generalize on abstract rules for reasoning?
    • Neural Dynamics of Object Manifold Alignment in the Ventral Stream
    • The hidden linear structure in score-based models and its application
    • Understanding Learning Dynamics of Neural Representations via Feature Visualization at Scale
    • Charting the Landscape of Ventral Stream Neural Code on Generative Image Manifolds
    • Diffusion models generate images like painters: an analytical theory of outline first, details later
    • On the Level Sets and Invariance of Neural Tuning Landscapes
    • Tuning landscapes of the ventral stream
    • High-performance Evolutionary Algorithms for Online Neuron Control
    • Factorized convolution models for interpreting neuron-guided images synthesis
    • On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation
    • The Geometry of Deep Generative Image Models and its Applications
    • Visual prototypes in the ventral stream are attuned to complexity and gaze behavior
    • What constitutes understanding of ventral pathway function?
    • A mechanism for synaptic copy between neural circuits
    • Mutual information and information gating in synfire chains
  • Projects
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    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
  • Projects
    • PyTorch
    • scikit-learn
    • Learn Python
  • Experience
  • Teaching
    • Neuro140/240 - Biological and Artificial Intelligence
    • Neuro 120 - Introduction to Computational Neuroscience
    • Machine Learning from Scratch
    • BIOL 5648 - Coding and Statistical Thinking in the Neurosciences
  • Academic notes
    • Note on Variants of Diffusion Scheduler, DDPM DDIM PNDM
    • Note on Hippo- Recurrent Memory with Optimal Polynomial Projection
    • Note on S4-Efficiently Modeling Long Sequences with Structured State Spaces
    • Note on Equivalent Score Matching Objective
    • Note on EM algorithm and likelihood lower bound
    • Note on Diffusion Generative Models
    • Probabilistic Models of Neural Population
    • Some Famous Matrix Determinant and Inversion Identities
    • Note on Kernel PCA
    • Analytical Techniques for Finding Spectrum of Tridiagonal Toeplitz Matrix
    • PCA of High Dimensional Trajectory
    • Note on Kernel Ridge Regression
    • Note on Hopfield Network
    • Note on Modern Hopfield Network and Transformers
    • Note on Feedback Stablization
    • Note on Bifurcation Normal Form
    • Note on Invariance and Stable Manifold
    • Note on Lyapnov Stability Theory
    • Note on Nonlinear Dynamic System
    • 2021-02-16-Alignment-of-Objective-in-Evolution
    • Note on Classic CNNs
    • A Model of Persistency
    • Note on Word2Vec
    • Note on Non-Parametric Regression
    • Note on Neural Tuning and Information
    • Note on Variational Inference (Updating)
    • Note on Bayesian Optimization
    • Note on Gaussian Process
    • Brief Note on Online Correlation Computation
    • Note on MinMax Game
    • Note on Laplacian Operator (Diffusion) in Geometry Processing
    • Note on Cortical Waves
    • Spectral Graph Theory and Segmentation
    • Computations on Hyperbolic Geometry
    • Note on Deep Reinforcement Learning
    • Note on Photometric Reasoning
    • Note on Generative Adversarial Network
    • Note on Computational Photography
    • Note on Hardware Based Computational Photography
    • Note on Epipolar Geometry and Optic Slow
    • Note on Semantic Vision Task
    • Note on Stereo Problem
    • Note on Image Prior-Markov Random Field Modelling
    • Note on Hessian Aware Zeroth Order Optimization Framework
    • Note on Advanced Computer Vision
    • Note on Image Prior-Spatial Relationship Modeling
    • 人间失格 读书札记
    • Understanding of Adversarial Attack
    • Krylov Subspace, Conjugate Gradient and Lancosz Iteration
    • Comparison of Major Deep Learning Frameworks (Updating)
    • Note on Online Linear Regression Algorithm
    • LBFGS Algorithm
    • Note on Visual Imagery
    • Note on Local Feature Descriptors
    • Note on ShapeCollage and Patch Based Shape Interpretation
    • Note on Categorization and Concepts
    • Some Computation on Sphere
    • Note on CNN Interpretability
    • Note on Forms of Memory
    • Note on Optimization on Manifold
    • Note on Fragment Based Object Recognition
    • Note on Feature Visualization (Updating)
    • Note on Deep Unsupervised Learning
    • Note on Animal Perception
    • Note on Computer Vision
    • Note on Behavioral Study
    • 真理的不同层级 (Updated)
    • 2019 台湾纪行
    • 进击的巨人(Attack on Titan) 观剧手记
    • Note on Network Commnunication
    • This Week's Learning about Brain 5 幻觉与笛卡尔的幽灵 Hallucination and Descartes' Demon (II)
    • This Week's Learning about Brain 4 看得见还是看不见, 这是一个问题——视觉意识的神经相关物 (To see or not to see, that's a question)
    • This Week's Learning about Brain 4 看得见还是看不见, 这是一个问题——视觉意识的神经相关物 (To see or not to see, that's a question)
    • Note on Algorithm for Non-Negative Matrix Factorization
    • Note on Computation by Synaptic Plasticity
    • Note on Selective Attention
    • Constrained CMA-ES Algorithm
    • Note on Belief Propagation Algorithm (Updating)
    • This Week's Learning about Brain 3 Hard Wired Olfactory Responce
    • This Week's Learning about Brain 2 Frequency Tuning of Hair Cell
    • Derivative Free Optimization Method (Based Feature Visulization) Notes 1
    • This Week's Learning about Brain 0
    • Some principles to establish a lifestyle
    • Antithesis
    • Distance-Matrix-Based
    • Image-Prior-Reading-Note
    • Note on Belief Propagation for Early Vision
    • Note on Generating Random Shapes
    • Note on VC Dimension
    • Note-on-Fitting-LNP
    • Note-on-Geodesic-and-Curvature
    • Note-on-Graph-Cut
    • Note-on-NEAT-CPPN
    • Note-on-Pareto-Front
    • Note-on-Smoothness-of-Function-on-Manifold
    • Note-on-SNR-for-Neuron
    • Note-on-StyleGAN
    • Note-on-Synaptic-Learning-Rules
    • Optimizer-Design-for-BigGAN
    • pandas_table_wrangling
  • Technical notes
    • Julia for Matlab and Python Users (Updating)
    • JavaScript + HTML Programming 101 (Updating)
    • MTurk 101
    • Scene Programming in MonkeyLogic2
    • Compiling C Extensions for PyTorch
    • Debugging StyleGAN2 in PyTorch
    • Publishing and Using Pretrained model through `Torch.hub`
    • GUI programming in Matlab
    • Hybrid Programming Matlab and Python
    • Importing Geometry from Google Map to Blender
    • Learning CMD / Shell Scripting in Windows
    • Show Animation in PDF Through Latex
    • Transporting Data Between Matlab, Python
    • Procedurally Generating Slides from Script
    • Handling and Printing Parameters in matlab
    • Note on Matlab and Python (matplotlib) Plotting system
    • Windows Working Environment Build Up (Updating)
    • Note on Pandas
    • Autograd Mechanism and Hessian Computation in PyTorch
    • Dynamic Visualization in Python
    • Computer Graphics Environment in Matlab
    • Multi-platform Matlab compiling
    • Working with Caffe
    • Using Google Cloud Service for Large Scale Image Labelling
    • How to Parse Anatomical/Physiological Terms in Latin/Greek
    • Linux Working Environment Build Up (Updating)
    • Understanding conda and python package management (Updating)
    • DeepLabCut Trouble Shooting
    • Common Statistical Problems in Neural Data Analysis (Updating)
    • Resources for Zebrafish Study
    • Note on Automatic 3D Instance Segmentation Pipeline
    • Automatic Behavioral Quantification Pipeline
    • How to translate matlab code into python (numpy)
    • Math Intensive Github Blog Construction
    • 3d-printing-tricks
    • Basic-Java-Concepts
    • Build-RL-Environment
    • Caffe-prototxt-format
    • Common-Recurrent-Modules
    • Compiling C Code for Python
    • Connecting Matlab and TF
    • Drawing-Meshes-in-Illustrator
    • Extracting WeChat Database
    • GUI-programming-python
    • Hacking Matlab Deep Learning
    • IO-Video-in-matlab-python
    • Music21_basics
    • NN_Training_Practicality
    • Note-on-Jax
    • Note_on_Optimizer_Development
    • pytest-usage
    • Python-Logging
    • Stanford-CoreNLP-Usage
    • Translating_TF_and_Torch
    • Vector-Figure-Editing-in-Illustrator

University of Chicago — NeuroML Workshop

Feb 20, 2026·
Binxu Wang
Binxu Wang
· 1 min read
Date
Feb 20, 2026
Event
NeuroML Workshop
Location

University of Chicago

Chicago, IL

Tutorial: Diffusion Models and Solvable Analytical Cases

Last updated on Feb 20, 2026
Diffusion Theory Science of AI NeuroAI
Binxu Wang
Authors
Binxu Wang
Research Fellow
← Flatiron Institute / CUNY — M.S. in Cognitive Science Special Seminar Mar 9, 2026
University of Minnesota — Department of Neuroscience Special Seminar Feb 16, 2026 →

© 2026 Me. This work is licensed under CC BY NC ND 4.0

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