Obtaining effective representations of DNA sequences is crucial for genome analysis.

Unsur-prisingly, however, models struggle to compose syntactically valid programs in programming languages unrepresented in pre-training, referred to as very low-resource Programming Languages (VLPLs).

Kernel k-means has been widely studied in machine learning.

Monte-Carlo tree search (MCTS) is an influential sequential decision-making algorithm notably employed in AlphaZero.

Generative Flow Networks (GFlowNets; GFNs) are a family of energy-based generative methods for combinatorial objects, capable of generating diverse and high-utility samples.

We provide theoretical guarantees for CBPR's rapid convergence to the optimal policy once human partners alter their policies.

Analyzing the motion of multiple biological agents, be it cells or individual animals, is pivotal for the understanding of complex collective behaviors. With the advent of advanced microscopy, detailed images of complex tissue formations involving multiple cell types have become more accessible in recent years. However, deciphering the underlying rules that govern cell movements is far from trivial.