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ablation-study · GitHub Topics · GitHub

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ablation-study

Here are 149 public repositories matching this topic...

Distribution transparent Machine Learning experiments on Apache Spark

  • Updated Feb 21, 2024
  • Python

This project implements 30+ variants of ANN algorithms to find the K nearest neighbors in high-dimensional vector spaces. It is meant as a convenient sandbox: drop in your own ANN code, run a one-liner, and instantly compare build/search speed and recall against the bundled baselines.

  • Updated Jan 22, 2026
  • C++

Testing whether models distinguish declared-true from declared-false premises

  • Updated Dec 22, 2025
  • Python

Attentively Embracing Noise for Robust Latent Representation in BERT (COLING 2020)

  • Updated Mar 1, 2021
  • Shell

Do Context Files Help Coding Agents? Two-agent (Claude Code + Codex) ablation on whether AGENTS.md/CLAUDE.md change coding-agent correctness & efficiency.

  • Updated Aug 2, 2026
  • Python

Adversarial security benchmark for agent authorization: does a compromised agent's policy-violating proposal become an unauthorized external effect? 73 trials, nine families, an independent oracle, per-mechanism ablation, confidence intervals. 0 unauthorized effects in 61 attack trials (95% CI [0.0%, 5.9%]). Reproduction is partial.

  • Updated Aug 4, 2026
  • Elixir

A light-weight library for fast-ablation studies on GPT-like Language Models.

  • Updated Aug 26, 2026
  • Python

O(N) attention with a bounded inference KV cache. D4 Daubechies wavelet field + content-gated Q·K gather at dyadic offsets.

  • Updated Jun 9, 2026
  • Python

This study tries to compare the detection of lung diseases using xray scans from three different datasets using three different neural network architectures using Pytorch and perform an ablation study by changing learning rates. The dimensional understanding is visualised using t-SNE and Grad-CAM for visualisation of diseases in x-ray scans.

  • Updated Jun 9, 2023
  • Jupyter Notebook

🧠 Automated neural network ablation studies using LLM agents and LangGraph. Systematically remove components, test performance, and gain insights into architecture importance through an intelligent multi-agent workflow.

  • Updated Mar 14, 2025
  • Python

Emotiwave is a research project investigating how well AI systems can recognise human emotions from video when one or more sensors fail. The core question: if you lose the audio, or the camera, or the transcript — does the system fall apart, or does it adapt?

  • Updated Mar 18, 2026
  • Jupyter Notebook

This project investigates the robustness of humanoid locomotion policies trained with imitation learning and reinforcement learning in simulation. The primary research question is: how does a learned PPO controller respond to partial actuator or degree-of-freedom failure, and which joints are most critical for maintaining stable locomotion?

  • Updated May 11, 2026
  • Python

Beautiful modular D3QN research pipeline with training, ablations, plots, report, and packaging

  • Updated Apr 30, 2026
  • Python

Reproducible research comparing GNN (GraphSAGE, GCN, GAT) vs ML baselines (XGBoost, RF) on Elliptic++ Bitcoin fraud detection. Features ablation experiments revealing when tabular models outperform graph neural networks.

  • Updated Nov 8, 2025
  • Python

Six Ways to Forget: Biologically-grounded forgetting mechanisms for LLM agent memory systems. 18 experiments, 4 falsified hypotheses, STDP ablation (Cohen's d = 3.163).

  • Updated Feb 20, 2026
  • Python

A comprehensive experimental lab for Looped Transformers from scratch. Includes an automated ablation pipeline (ExperimentTable) and a real-time monitoring dashboard.

  • Updated Jun 22, 2026
  • Jupyter Notebook

A multimodal deep learning project for classifying mental health-related memes, combining both textual and visual features.

  • Updated May 7, 2025
  • Jupyter Notebook

From-scratch GPT-2 124M reproduction, every figure pinned to an artifact by CI: 3.0503 val loss against a pre-registered 3.29, HellaSwag 0.3043, a paired-seed ablation study, and 95.1% scaling on 8 GPUs.

  • Updated Aug 26, 2026
  • Python

CIFAR-10 from scratch in PyTorch — ResNet-18 with no pretrained weights, 96.06% test top-1, every recipe decision backed by a logged ablation.

  • Updated Aug 12, 2026
  • Python

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