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Found 5 papers, 1 papers with code
An Interdisciplinary Outlook on Large Language Models for Scientific Research
In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision.
Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality
A novel Policy Gradient (PG) algorithm, called Matryoshka Policy Gradient (MPG), is introduced and studied, in the context of max-entropy reinforcement learning, where an agent aims at maximising entropy bonuses additional to its cumulative rewards.
Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning
With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density.
DeC and ADER: Similarities, Differences and a Unified Framework
Finally, in the numerical section we investigate A-stability for the ADER approach - this is done for the first time up to our knowledge - for different order using several basis functions and compare them with the DeC ansatz.
Numerical Analysis Numerical Analysis
What do Language Representations Really Represent?
If the corpus is multilingual, the same model can be used to learn distributed representations of languages, such that similar languages end up with similar representations.
