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Experimental Design

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/jenniferbrennan/CountingDiscoveries

공식 코드

Estimating the number and effect sizes of non-null hypotheses

https://github.com/jsalt2024-evaluating-llms-for-astronomy/astro-arxiv-bot

공식 코드

Designing an Evaluation Framework for Large Language Models in Astronomy Research

https://github.com/kanishkg/boxing-gym

공식 코드

BoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery

https://github.com/kasia-kobalczyk/active-task-disambiguation

공식 코드

Active Task Disambiguation with LLMs

https://github.com/lai1997/bmlp_active_public

공식 코드

Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models

https://github.com/lamalab-org/mac-bench

공식 코드

Probing the limitations of multimodal language models for chemistry and materials research

https://github.com/lasterminator/cpsc-8570-network-technologies-security

공식 코드

A Novel Approach to Guard from Adversarial Attacks using Stable Diffusion

https://github.com/lauritowal/ai-ai-bias

공식 코드

AI AI Bias: Large Language Models Favor Their Own Generated Content

https://github.com/levishery/accelerateoed

공식 코드

Neural Message Passing for Objective-Based Uncertainty Quantification and Optimal Experimental Design

https://github.com/lhirschfeld/ChempropUncertaintyQuantification

공식 코드

Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

https://github.com/liuyue002/woundhealing

공식 코드

Parameter identifiability and model selection for partial differential equation models of cell invasion

https://github.com/lsarra/active-learning

공식 코드

Deep Bayesian Experimental Design for Quantum Many-Body Systems

https://github.com/lukasmut/vice

공식 코드

VICE: Variational Interpretable Concept Embeddings

https://github.com/m3rg-iitd/aila

공식 코드

Autonomous Microscopy Experiments through Large Language Model Agents

https://github.com/mChataign/DupireNN

공식 코드

Deep Local Volatility

https://github.com/maxramgraber/triangular-transport-toolbox

공식 코드

A friendly introduction to triangular transport

https://github.com/mb-29/exploration

공식 코드

FLEX: an Adaptive Exploration Algorithm for Nonlinear Systems

https://github.com/mb-29/greedy-identification

공식 코드

Online greedy identification of linear dynamical systems

https://github.com/mcleish7/gemstone-scaling-laws

공식 코드

Gemstones: A Model Suite for Multi-Faceted Scaling Laws

https://github.com/mhinne/BNQD

공식 코드

Bayesian nonparametric discontinuity design

https://github.com/microsoft/EDDI

공식 코드

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

https://github.com/microsoft/co-bed

공식 코드

CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

https://github.com/mjarvenpaa/parallel-GP-SL

공식 코드

Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations

https://github.com/mjcolebank/Colebank_Identifiability_PDE

공식 코드

Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction

https://github.com/mlindauer/GenericWrapper4AC

공식 코드

Pitfalls and Best Practices in Algorithm Configuration

https://github.com/mmorafah/fedzoo-bench

공식 코드

A Practical Recipe for Federated Learning Under Statistical Heterogeneity Experimental Design

https://github.com/mojusko/sensepy

공식 코드

Sensing Cox Processes via Posterior Sampling and Positive Bases

https://github.com/mschulth/rhc

공식 코드

Receding Horizon Curiosity

https://github.com/multimedia-berkeley/deep_thoughts

공식 코드

A Capacity Scaling Law for Artificial Neural Networks

https://github.com/ndif-team/nnsight

공식 코드

NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals

https://github.com/neu-spiral/AcceleratedExperimentalDesign

공식 코드

Accelerated Experimental Design for Pairwise Comparisons

https://github.com/oagarwal/temporal-effects

공식 코드

Temporal Effects on Pre-trained Models for Language Processing Tasks

https://github.com/open-sciencelab/social_science

공식 코드

Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System

https://github.com/open-sciencelab/virtual-scientists

공식 코드

Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System

https://github.com/opencobra/cobratoolbox

공식 코드

Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0

https://github.com/phelps-sg/llm-cooperation

공식 코드

The Machine Psychology of Cooperation: Can GPT models operationalise prompts for altruism, cooperation, competitiveness and selfishness in economic games?

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.