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Name: Stanislav Fort
Type: User
Bio: PhD student at Stanford | ML, AI & Physics
Name: Stanislav Fort
Type: User
Bio: PhD student at Stanford | ML, AI & Physics
Adversarial examples to the new ConvNeXt architecture
Annual computing Boot Camp for new (and other) KIPAC members
A classical (non-quantum) implementation of the Grover's algorithm (quantum)
A collection of tips and tricks for data visualization in Python.
Deep reinforcement learning for the board game Pylos
Replicating and dissecting the git-re-basin project in one-click-replication Colabs
Reproducing plots and loss landscape cuts from the paper *Deep Ensembles: A Loss Landscape Perspective* (https://arxiv.org/abs/1912.02757)
Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanislav Fort, Jie Ren, Balaji Lakshminarayanan, published at NeurIPS 2021.
A template for really easy blogging with GitHub Pages
Gaussian prototypical network architecture for few-shot learning
...with git and GitHub
Generating 3D Hilbert curves
Assorted experiments to verify the connectivity of DNN initializations to optima in the weight space
An example of a large language model finetuning on MNIST and CIFAR-10
Trying to make the Apple Byteformer work
A character-level probabilistic language generator based on Markov chains
Replicating the basic adversarial multi-attack experimental results
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Developing adversarial examples and showing their semantic generalization for the OpenAI CLIP model (https://github.com/openai/CLIP)
Software developer resume in Latex
Training DNNs on data with singular values removed / kept, testing on similarly modified test sets
Code to replicate the key findings of the paper /What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries/
A research blog on machine learning, artificial intelligence and physics
Computation using data flow graphs for scalable machine learning
The Ulam prime spiral generator
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.