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Found 7 papers, 6 papers with code
AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models
We present AstroCLIP, a strategy to facilitate the construction of astronomical foundation models that bridge the gap between diverse observational modalities.
Multiple Physics Pretraining for Physical Surrogate Models
We introduce multiple physics pretraining (MPP), an autoregressive task-agnostic pretraining approach for physical surrogate modeling.
xVal: A Continuous Number Encoding for Large Language Models
Large Language Models have not yet been broadly adapted for the analysis of scientific datasets due in part to the unique difficulties of tokenizing numbers.
Reusability report: Prostate cancer stratification with diverse biologically-informed neural architectures
This suggests that different neural architectures are sensitive to different aspects of the data, an important yet under-explored challenge for clinical prediction tasks.
An online algorithm for contrastive Principal Component Analysis
However, the performance of cPCA is sensitive to hyper-parameter choice and there is currently no online algorithm for implementing cPCA.
Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy
The network we derive does not involve one-to-one connectivity or signal multiplexing, which the phenomenological models required, indicating that these features are not necessary for learning in the cortex.
Neural circuits for dynamics-based segmentation of time series
In particular, the segmentation accuracy is similar to that obtained from oracle-like methods in which the ground-truth parameters of the autoregressive models are known.
