HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Formation Energy
Formation Energy On Gete
Formation Energy On Gete
Metrics
MAE
Results
Performance results of various models on this benchmark
Columns
Model Name
MAE
Paper Title
BOTNet
3034
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
MACE
2670
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
NequIP
1780.951
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
Allegro
1009.4
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
0 of 4 row(s) selected.
Previous
Next
HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Formation Energy
Formation Energy On Gete
Formation Energy On Gete
Metrics
MAE
Results
Performance results of various models on this benchmark
Columns
Model Name
MAE
Paper Title
BOTNet
3034
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
MACE
2670
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
NequIP
1780.951
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
Allegro
1009.4
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
0 of 4 row(s) selected.
Previous
Next