MT-ENet
importedtherapeutics/mt-enet
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Therapeutics
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- deargen
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/deargen/MT-ENet
- Documentation
- unknown
- Tags
- aaai · bayesian-neural-networks · deep-learning · drug-discovery · drug-target-interactions · empirical-bayes · evidential-deep-learning · machine-learning · multitask-learning · pytorch · uncertainty-estimation · uncertainty-quantification
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- chempropdrug-discovery · evidential-deep-learning
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
- BayesCapuncertainty-estimation · uncertainty-quantification
(ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
- CaliBrainuncertainty-estimation · uncertainty-quantification
Python toolbox for uncertainty estimation and calibration in EEG/MEG inverse source imaging.
- hyper-dtidrug-discovery · drug-target-interactions · pytorch
HyperPCM: Robust task-conditioned modeling of drug-target interactions
- ssvep-multi-task-learningmultitask-learning · pytorch
Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free…
- uq4dddrug-discovery · uncertainty-quantification
UQ4DD: Uncertainty Quantification for Drug Discovery
- api.github.com/repos/deargen/MT-ENetretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2022-03-04, 20 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/13.json→ .entries["mt-enet"]
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