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홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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소개
한국어
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  1. 홈
  2. SOTA
  3. 약물 탐색
  4. Drug Discovery On Tox21

Drug Discovery On Tox21

평가 지표

AUC

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
AUC
Paper TitleRepository
ContextPred0.781Strategies for Pre-training Graph Neural Networks
GraphConv + dummy super node0.854Learning Graph-Level Representation for Drug Discovery
TrimNet0.860TrimNet: learning molecular representation from triplet messages for biomedicine-
RNN-DFS0.748Relational Pooling for Graph Representations
GraphConv0.846Convolutional Networks on Graphs for Learning Molecular Fingerprints
Ensemble predictor0.862ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors-
elEmBERT-V10.961Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties
GIT-Mol(G+S)0.759GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
SNN (SELU Network)0.845Self-Normalizing Neural Networks
SSVAE with multiple SMILES0.871All SMILES Variational Autoencoder-
TrimNet + Perforated Backpropagation0.885Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
0 of 11 row(s) selected.
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한국어

소개

회사 소개데이터셋 도움말

제품

뉴스튜토리얼데이터셋백과사전

링크

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