AI models
Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation
Published
Aug 19, 2024
Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation is an AI model developed by ETH Zurich, University of Zurich and ETH AI Center (Switzerland), first published in August 2024. It works in the biology domain, on tasks such as drug discovery.
Epoch AI has no training-compute estimate for this model. Training ran on 1 NVIDIA GeForce RTX 4090.
Access: Open weights (non-commercial). Its weights are openly available. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- ETH Zurich, University of Zurich, ETH AI Center
- Country of organization
- Switzerland
- Domain
- Biology
- Task
- Drug discovery
- Compute estimation method
- Hardware
- Training hardware
- NVIDIA GeForce RTX 4090
- Chips used
- 1
- Training power draw
- 487 W
- Model accessibility
- Open weights (non-commercial)
- Open weights
- Yes
- Citations
- 0
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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