65 citations · 149 across the 17 of their papers we have counts for
5 papers · 1 filter
Continuous Monte Carlo Graph Search
Kalle Kujanpää, Amin Babadi, Yi Zhao +3
Online planning is crucial for high performance in many complex sequential decision-making tasks. Monte Carlo Tree Search (MCTS) employs a principled mechanism for trading off expl…
Compositional Generalization in Grounded Language Learning via Induced Model Sparsity
Sam Spilsbury, Alexander Ilin
We provide a study of how induced model sparsity can help achieve compositional generalization and better sample efficiency in grounded language learning problems. We consider simp…
Learning Trajectories of Hamiltonian Systems with Neural Networks
Katsiaryna Haitsiukevich, Alexander Ilin
Modeling of conservative systems with neural networks is an area of active research. A popular approach is to use Hamiltonian neural networks (HNNs) which rely on the assumptions t…
Improved Training of Physics-Informed Neural Networks with Model Ensembles
Katsiaryna Haitsiukevich, Alexander Ilin
Learning the solution of partial differential equations (PDEs) with a neural network is an attractive alternative to traditional solvers due to its elegance, greater flexibility an…
Precise atom manipulation through deep reinforcement learning
I-Ju Chen, Markus Aapro, Abraham Kipnis +3
Atomic-scale manipulation in scanning tunneling microscopy has enabled the creation of quantum states of matter based on artificial structures and extreme miniaturization of comput…