XujieSi

XujieSi's Stars

• noah-nuebling/mac-mouse-fix

  Mac Mouse Fix - Make Your $10 Mouse Better Than an Apple Trackpad!

  Language:Objective-C5.4k37912150

• leanprover/lean4

  Lean 4 programming language and theorem prover

  Language:Lean4.5k671.8k403

• google-deepmind/alphatensor

  Language:Python2.7k5711233

• igrigorik/gharchive.org

  GH Archive is a project to record the public GitHub timeline, archive it, and make it easily accessible for further analysis.

  Language:Ruby2.7k75199206

• github/CodeSearchNet

  Datasets, tools, and benchmarks for representation learning of code.

  Language:Jupyter Notebook2.2k6061386

• BinaryAnalysisPlatform/bap

  Binary Analysis Platform

  Language:OCaml2.1k93493273

• mthom/scryer-prolog

  A modern Prolog implementation written mostly in Rust.

  Language:Rust2k531.6k117

• leanprover-community/mathlib4

  The math library of Lean 4

  Language:Lean1.4k38398313

• kundajelab/deeplift

  Public facing deeplift repo

  Language:Python8183789162

• mahsu/MariOCaml

  HTML 5 canvas implementation of Mario written in Ocaml

  Language:OCaml542274110

• reasonml-community/Mareo

  HTML 5 canvas implementation of Mario in Reason + Bucklescript

  Language:JavaScript3837344

• TiarkRompf/virtualization-lms-core

  A Framework for Runtime Code Generation and Compiled DSLs

  Language:Scala323404991

• GitGyun/visual_token_matching

  [ICLR'23 Oral] Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching

  Language:Python25271714

• PLSysSec/sys

  Sys: A Static/Symbolic Tool for Finding Good Bugs in Good (Browser) Code

  Language:LLVM220232741

• leanprover-community/lean4-metaprogramming-book

  Language:Lean212103953

• ocaml-gospel/gospel

  A tool-agnostic formal specification language for OCaml.

  Language:OCaml126910016

• breandan/galoisenne

  🕸️ Graphs, finite fields and discrete dynamical systems in Kotlin

  Language:Kotlin115748

• leanprover-community/ProofWidgets4

  Helper toolkit for creating your own Lean 4 UserWidgets

  Language:Lean10572026

• cssho/vscode-svgviewer

  SVG Viewer for Visual Studio Code

  Language:TypeScript6784120

• leanprover-community/iris-lean

  Lean 4 port of Iris, a higher-order concurrent separation logic framework

  Language:Lean632635

• dbtsai/libDAI

  A free and open source C++ library for Discrete Approximate Inference in graphical models

  Language:C++505325

• hopv/MoCHi

  MoCHi: Model Checker for Higher-Order Programs

  Language:OCaml41525

• caterinaurban/Lyra

  Language:Python2942411

• snap-stanford/zeroc

  ZeroC is a neuro-symbolic method that trained with elementary visual concepts and relations, can zero-shot recognize and acquire more complex, hierarchical concepts, even across domains

  Language:Jupyter Notebook294824

• satwik77/Transformer-Formal-Languages

  EMNLP 2020: On the Ability and Limitations of Transformers to Recognize Formal Languages

  Language:Python242010

• tud-ccc/compy-learn

  ComPy-Learn is a framework for exploring program representations for ML4CODE tasks.

  Language:Python22649

• marekpiotrow/UWrMaxSat

  UWrMaxSat is a relatively new MiniSat+-based solver participating in MaxSAT Evaluation 2019, where it ranked second places in both main tracks (weighted and unweighted). In MaxSAT Evaluation 2020 it won the weighted main track. It has been created recently at the University of Wrocław. It is a complete solver for partial weighted MaxSAT instances and pseudo-Boolean ones. It incrementally uses COMiniSatPS by Chanseok Oh (2016) as an underlying SAT solver, but may be compiled with other MiniSat-like solvers. It was developed on the top of our PB-solver (called kp-minisatp) that was presented at Pragmatics of SAT 2018 and which is an extension of the well-known MiniSat+ solver. In its main configuration, UWrMaxSat applies an unsatisfiability-core-based OLL procedure and uses the kp-minisatp sorter-based pseudo-Boolean constraint encoding to translate new cardinality constraints into CNF.

  Language:C++213103

• jenellefeather/model_metamers_pytorch

  Code for paper "Model metamers reveal divergent invariances between biological and artificial neural networks." Feather et al. 2023

  Language:Python13213

• rebryant/pgbdd-artifact

  Demonstration of BDD-based SAT solver that generates checkable proofs of unsatisfiability. Details provided in paper: R. E. Bryant and M. J. H. Heule, "Generating Extended Resolution Proofs in a BDD-based SAT Solver," TACAS 2021

  Language:Python7200

• chwwhc/MicroGrammarChecker

  Repo for my COMP 400 project

  Language:Haskell213