3 citations · 8 across the 6 of their papers we have counts for
6 papers
ViewFusion: Learning Composable Diffusion Models for Novel View Synthesis
Bernard Spiegl, Andrea Perin, Stéphane Deny +1
Deep learning is providing a wealth of new approaches to the problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end style architectures.…
Quantum Gate Optimization for Rydberg Architectures in the Weak-Coupling Limit
Nicolas Heimann, Lukas Broers, Nejira Pintul +5
We demonstrate machine learning assisted design of a two-qubit gate in a Rydberg tweezer system. Two low-energy hyperfine states in each of the atoms represent the logical qubit an…
Hierarchical Imitation Learning with Vector Quantized Models
Kalle Kujanpää, Joni Pajarinen, Alexander Ilin
The ability to plan actions on multiple levels of abstraction enables intelligent agents to solve complex tasks effectively. However, learning the models for both low and high-leve…
Learning Explicit Object-Centric Representations with Vision Transformers
Oscar Vikström, Alexander Ilin
With the recent successful adaptation of transformers to the vision domain, particularly when trained in a self-supervised fashion, it has been shown that vision transformers can l…
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
Yi Zhao, Rinu Boney, Alexander Ilin +2
Offline reinforcement learning, by learning from a fixed dataset, makes it possible to learn agent behaviors without interacting with the environment. However, depending on the qua…
A Relational Model for One-Shot Classification
Arturs Polis, Alexander Ilin
We show that a deep learning model with built-in relational inductive bias can bring benefits to sample-efficient learning, without relying on extensive data augmentation. The prop…