Papers with Code 아카이브

Equation Discovery

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/IBM/AI-Hilbert

공식 코드

Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI Hilbert

https://github.com/ITMO-NSS-team/EPDE_automated_knowledge

공식 코드

Knowledge-aware equation discovery with automated background knowledge extraction

https://github.com/ITMO-NSS-team/EPDE_paper_experiments

공식 코드

Equation discovery framework EPDE: Towards a better equation discovery

https://github.com/alpz/mech-nn

공식 코드

Mechanistic Neural Networks for Scientific Machine Learning

https://github.com/brencej/ProGED

공식 코드

Probabilistic Grammars for Equation Discovery

https://github.com/carolinepacheco/equation-discovery-scene-analysis

공식 코드

Automated Mathematical Equation Structure Discovery for Visual Analysis

https://github.com/carolinepacheco/equation_discovery_scene_analysis

공식 코드

Automated Mathematical Equation Structure Discovery for Visual Analysis

https://github.com/charlesdelahunt/sindytoolkitforhighnoise

공식 코드

A toolkit for data-driven discovery of governing equations in high-noise regimes

https://github.com/deep-symbolic-mathematics/Multimodal-Math-Pretraining

공식 코드

SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training

https://github.com/deep-symbolic-mathematics/Multimodal-Symbolic-Regression

공식 코드

SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training

https://github.com/deep-symbolic-mathematics/TPSR

공식 코드

Transformer-based Planning for Symbolic Regression

https://github.com/deep-symbolic-mathematics/llm-sr

공식 코드

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

https://github.com/deep-symbolic-mathematics/llm-srbench

공식 코드

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

https://github.com/envfluids/MEDIDA

공식 코드

Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case

https://github.com/envfluids/py2d

공식 코드

Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges

https://github.com/epfl-imos/sym-q

공식 코드

Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework

https://github.com/gnorman7/constrained_nn_eq_discovery

공식 코드

Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data

https://github.com/hbhat4000/learningpotentials

공식 코드

Learning and Interpreting Potentials for Classical Hamiltonian Systems

https://github.com/ibm/ai-descartes

공식 코드

AI Descartes: Combining Data and Theory for Derivable Scientific Discovery

https://github.com/intell-sci-comput/pts

공식 코드

Discovering symbolic expressions with parallelized tree search

https://github.com/itmo-nss-team/cec_2023_knowledge

공식 코드

Directed differential equation discovery using modified mutation and cross-over operators

https://github.com/itmo-nss-team/epde_gecco_experiments

공식 코드

Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery

https://github.com/itmo-nss-team/klr2023_paper

공식 코드

Towards true discovery of the differential equations

https://github.com/jakharkaran/eqsdiscovery_2d-fhit_rbc

공식 코드

Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges

https://github.com/jiankeyang/laligan

공식 코드

Latent Space Symmetry Discovery

https://github.com/long-da/kbass

공식 코드

Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels

https://github.com/luningsun/splinelearningequation

공식 코드

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

https://github.com/mathbiocu/wsindy_cellcluster

공식 코드

Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population

https://github.com/menggedu/edl

공식 코드

LLM4ED: Large Language Models for Automatic Equation Discovery

https://github.com/nisalr/ginn-lp

공식 코드

GINN-LP: A Growing Interpretable Neural Network for Discovering Multivariate Laurent Polynomial Equations

https://github.com/pongpisit-thanasutives/parametric-discovery

공식 코드

Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery

https://github.com/punkduckable/PDE-READ

공식 코드

PDE-READ: Human-readable Partial Differential Equation Discovery using Deep Learning

https://github.com/punkduckable/pde-extraction

공식 코드

PDE-READ: Human-readable Partial Differential Equation Discovery using Deep Learning

https://github.com/rose-stl-lab/symmetry-ode-discovery

공식 코드

Symmetry-Informed Governing Equation Discovery

https://github.com/tee-lab/pydaddy

공식 코드

Discovering stochastic dynamical equations from biological time series data

https://github.com/theobourdais/computationalhypergraphdiscovery

공식 코드

Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots

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