CONFIDENCE EVALUATION MODEL FOR STRUCTURE PREDICTION TASKS

CONFIDENCE EVALUATION MODEL FOR STRUCTURE PREDICTION TASKS

Techniques for training for and determining a confidence of an output of a machine learning model are disclosed. Such techniques include, in some embodiments, receiving, from the machine learning model configured to receive information associated with a data object, information associated with a pre...

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Bibliographische Detailangaben
Hauptverfasser: Tensmeyer, Christopher, Madapoosi Ravi, Sruthi, Mathur, Priyank, Barmpalios, Nikolaos, Deshpande, Ruchi, Bangalore Naresh, Smitha, Sido, Oghenetegiri, Manjunatha, Varun
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung:Techniques for training for and determining a confidence of an output of a machine learning model are disclosed. Such techniques include, in some embodiments, receiving, from the machine learning model configured to receive information associated with a data object, information associated with a predicted structure for the data object; encoding, using a second machine learning model, the information associated with the predicted structure for the data object to produce encoded input channels; evaluating, using the second machine learning model, the information associated with the data object with the encoded input channels; and based on the evaluating, determining, using the second machine learning model, a probability of correctness of the predicted structure for the data object.