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NVIDIA
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09:20
(UTC -12:00) - nblauch.github.io
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foveal/peripheral vision simulator in a web browser
Foveated vision interface for deep vision models
AI agents running research on single-GPU nanochat training automatically
A platform for reproducible world model research and evaluation
Unified framework for robot learning built on NVIDIA Isaac Sim
OpenShell is the safe, private runtime for autonomous AI agents.
[Nature Machine Intelligence 2025] Emulating Human-like Adaptive Vision for Efficient and Flexible Machine Visual Perception
A PyTorch Implementation of "Recurrent Models of Visual Attention"
gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI
Do deep neural networks have visual illusions?
Hyperalignment(Haxby et al., 2011) tutorial
Code for the manim-generated scenes used in 3blue1brown videos
HellaSwag: Can a Machine _Really_ Finish Your Sentence?
Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning (CVPR2020)
official code repository for the paper "Dissecting Query-Key Interaction in Vision Transformers"
Evaluate computational models on their alignment to behavioral and neural measurements in the domain of language
Topoformer: brain-like topographic organization in Transformer language models through spatial querying and reweighting
onavg is a cortical surface template that was created based on high-quality structural scans of 1,031 brains from OpenNeuro
Rebuild the Stable Diffusion Model in a single python script. Tutorial for Harvard ML from Scratch Series
A few CLI tools to immersively, browse, read Arxiv paper, save to notion & zotero, chat with them and save the chat history
Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections (NeurIPS 2023)
Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)
Official repository for the paper "Behavior measures are predicted by how information is encoded in an individual’s brain"
Learning low-shot object classification with explicit shape bias learned from point clouds