HSE CS Open Source

A collection of open-source projects and resources created by HSE CS staff and students, including research code, courses, and other educational and technical resources.

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Projects by Year

Projects are organized by the year they were released or published.

2026

• Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation (ICML2026) — Smoothie, paper (2026)
• SynEL: A synthetic benchmark for entity linking - SynEL, paper (2026)
• Benchmarking Optimizers for MLPs in Tabular Deep Learning - tabular-dl-optimizers, paper (2026)
• Turning Tabular Foundation Models into Graph Foundation Models - G2T-FM, paper (2026)
• MiAD: Mirage Atom Diffusion for De Novo Crystal Generation - MiAD, paper (2026)
• ML2B: Multi-Lingual ML Benchmark For AutoML - ML2B, paper (2026)
• Multimodal graph, surface, and language-based model for protein protein interaction prediction - gsmformer-ppi, paper (2026)
• (Re)defining the human chromatome: an integrated meta-analysis of localization, function, abundance, physical properties, and domain composition of chromatin proteins - SimChrom, paper (2026)
• GeomMotif: A Benchmark for Arbitrary Geometric Preservation in Protein Generation - GeomMotif, paper (2026)
• Modeling Pruning as a Phase Transition: A Thermodynamic Analysis of Neural Activations - Activation_Pruning, paper (2026)
• DPN Verifier: A Toolkit for Faster Soundness Verification and Repair of Process Models with Data - DPNVerifier, paper (2026)
• RTCMS4J: Easily control your Spring applications in real-time! - hse-rtcms4j (2026)
• HoTPP benchmark: Are we good at the long horizon events forecasting? - hotpp-benchmark, paper (2026)
• CasTex: Cascaded Text-to-Texture Synthesis via Explicit Texture Maps and Physically-Based Shading - CasTex, paper (2026)
• Online Neural Networks for Change-Point Detection - Roerich, paper (2026)

2025

• COSMOS: Compressed and Smooth Latent Space for Text Diffusion Modeling (NeurIPS2025) — COSMOS, paper (2025)
• MaterialFusion: High-Quality, Zero-Shot, and Controllable Material Transfer with Diffusion Models (CVPR2025) — MaterialFusion, paper (2025)
• TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling - TabM, paper (2025)
• I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders - SAE-Reasoning, paper (2025)
• Hogwild! Inference: Parallel LLM Generation via Concurrent Attention - hogwild_llm, paper (2025)
• TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings - TEncDM, paper (2025)
• On Finetuning Tabular Foundation Models - tabpfn-finetuning, paper (2025)
• When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs - when-punctuation-matters, paper (2025)
• ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations - ProcrustesGPT, paper (2025)
• Tight Bounds for Schrödinger Potential Estimation in Unpaired Image-to-Image Translation Problems - Tight Bounds for Schrödinger Potential Estimation, paper (2025)
• gfnx: Fast and Scalable Library for Generative Flow Networks in JAX - gfnx, paper (2025)
• Deep-learning-based Identification of Solar Magnetic Tornadoes and Their Spatial Properties during Solar Minimum and Maximum - solar-magnetic-tornado, paper (2025)
• Performance Modeling of Data Storage Systems Using Generative Models - digital-twin, paper (2025)
• Knowledge Graph Completion with Mixed Geometry Tensor Factorization - MIGTF, paper (2025)
• Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation - PersonGenSampler, paper (2025)
• Enhancing FEVER-Style Claim Fact-Checking Against Wikipedia: A Diagnostic Taxonomy and a Generative Framework - FEVERDiagnostics, paper (2025)
• Matrix-Free Two-to-Infinity and One-to-Two Norms Estimation - TwoToInfinity, paper (2025)
• CLEAR: Character Unlearning in Textual and Visual Modalities - multimodal_unlearning, paper (2025)
• Revisiting Non-Acyclic GFlowNets in Discrete Environments - non-acyclic-gfn, paper (2025)
• PaGLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebrasper - PaGLGENN, paper (2025)
• AutoJudge: Judge Decoding Without Manual Annotation - AutoJudge, paper (2025)
• Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization - gflownet-tlm, paper (2025)
• Prediction of protein-protein interactions using point transformer and spherical Convex Hull graphs - PT-PPI, paper (2025)
• Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models - aquakv, paper (2025)
• Efficient incorporation of new interactions in graph recommenders via folding-in - Folding-In-MRGSRec, paper (2025)
• LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters - RiemanianFinetune, paper (2025)
• Robotics manipulator that will be able to play table tennis - Mr.Handy (2025)

2024

• Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space - WU-GO, paper (2024)
• TabReD: A Benchmark of Tabular Machine Learning in-the-Wild - TabReD, paper (2024)
• Extracting high-level activities from low-level program execution logs - Procfiler, paper (2024)
• Linguacodus: a synergistic framework for transformative code generation in machine learning pipelines - Linguacodus, paper (2024)
• The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN Inversion and High Quality Image Editing - StyleFeatureEditor, paper (2024)
• Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula - gen-simplicial-cycles, paper (2024)
• Truth-O-Meter: Handling Multiple Inconsistent Sources Repairing LLM Hallucinations - Truth-O-Meter, paper (2024)
• Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing - Guide-and-Rescale, paper (2024)
• Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers - TensorNorm, paper (2024)
• Highly Accurate Method for Detecting Archaic Segments in the Modern Genomes - DAIseg, paper (2024)
• Where Do Large Learning Rates Lead Us? - understanding-largre-lrs, paper (2024)
• Inertia-Based Indices to Determine the Number of Clusters in K-Means: An Experimental Evaluation - Indecies-kmeans, paper (2024)
• TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features - TabGraphs, paper (2024)
• Differentiable Rendering with Reparameterized Volume Sampling - reparameterized-volume-sampling, paper (2024)
• RatanSunPy: A robust preprocessing pipeline for RATAN-600 solar radio observations data - RATANSunPy, paper (2024)
• Z-DNA formation in promoters conserved between human and mouse are associated with increased transcription reinitiation rates - DeepZ_MM, paper (2024)
• Accuracy Certificates for Convex Minimization with Inexact Oracle - vaidya-with-certificates, paper (2024)
• Your Transformer is Secretly Linear - LLM-Microscope, paper (2024)
• Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps - invertible-cd, paper (2024)
• Challenges of Generating Structurally Diverse Graphs - Challenges-on-generating-structurally-diverse-graphs, paper (2024)
• Understanding admixture fractions: theory and estimation of gene-flow - QuAP, paper (2024)
• Approach to creating the service for code generation ofmobile applicationsusing the large language models - CodeBuddy, paper (2024)
• GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data - GraphLand, paper (2024)
• Verification of data-aware process models: Checking soundness of data Petri nets - DPN-Soundness-Verification, paper (2024)
• An Analysis of Sequential Patterns in Datasets for Evaluation of Sequential Recommendations - Does-It-Look-Sequential, paper (2024)
• MELINDA is a python library for creating tabular synthetic data. - Linda (2024)
• Truck is an open source project dedicated to the construction and development of the 2.5D indoor autonomous vehicle based on the ackermann steering model - Truck (2024)
• Probaforms is a python library of conditional generative models for tabular data. - Probaforms (2024)

2023

• Understanding of the properties of neural network approaches for transient light curve approximations - Fulu, paper (2023)
• TabDDPM: Modelling Tabular Data with Diffusion Models - TabDDPM, paper (2023)
• Star-Shaped Denoising Diffusion Probabilistic Models - Star-Shaped DDPM, paper (2023)
• Generative Flow Networks as Entropy-Regularized RL - gflownet-rl, paper (2023)
• MARS: Masked Automatic Ranks Selection in Tensor Decompositions - MARS, paper (2023)
• TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning - TabR, paper (2023)
• Sparse representation for machine learning the properties of defects in 2D materials - MegNetSparse, paper (2023)
• Predicting Molecule Toxicity via Descriptor-Based Graph Self-Supervised Learning - GNN-Tox, paper (2023)
• Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts - structural-graph-shifts, paper (2023)
• Generic flexibility of affine cones over del Pezzo surfaces in Sagemath - delPezzo, paper (2023)
• A critical look at the evaluation of GNNs under heterophily: Are we really making progress? - heterophilous-graphs, paper (2023)
• Sparse representation for machine learning the properties of defects in 2D materials - ai4material_design, paper (2023)
• Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics - DVAR, paper (2023)

2022

• Estimating the timing of multiple admixture events using 3-locus linkage disequilibrium - LaNeta, paper (2022)
• On Embeddings for Numerical Features in Tabular Deep Learning - rtdl-num-embeddings, paper (2022)
• HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks - HyperDomainNet, paper (2022)
• Self-supervised recurrent depth estimation with attention mechanisms - self-supervised-depth-estimation, paper (2022)
• Community Detection in Feature-Rich Networks Using Data Recovery Approach - SEFNAC_Alg, paper (2022)
• Variance reduction for additive functionals of Markov chains via martingale representations - MAD-CV, paper (2022)
• CartPole control experiments - CartPole (2022)

2021

• Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation (ICCV2021) — C-PIC, paper (2021)
• VGsim: scalable viral genealogy simulator for global pandemic - VGsim, paper (2021)
• Secure Distributed Training at Scale - btard, paper (2021)
• Landmarks Augmentation with Manifold-Barycentric Oversampling - LAMBO, paper (2021)

2020

• Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation - TIRE, paper (2020)
• GP-VAE: Deep Probabilistic Time Series Imputation - GP-VAE, paper (2020)
• Adaptive divergence for rapid adversarial optimization - rapid-ao, paper (2020)

2009

• Automatic Relevance Determination for Gaussian Mixture Models - ARD-EM (2009)

Contributing

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