906 citations
- University of TorontoCA28 papers
- Centre National de la Recherche ScientifiqueFR15 papers
- Centre de physique des particules de MarseilleFR14 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR14 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR14 papers
- Laboratoire de Physique Nucléaire et de Hautes ÉnergiesFR14 papers
- Las Cumbres Observatory Global Telescope NetworkUS14 papers
- University of California, Santa BarbaraUS14 papers
- University of VictoriaCA14 papers
- Astronomical Observatory of RomeIT12 papers
- Australian Astronomical ObservatoryAU12 papers
- University of Colorado BoulderUS12 papers
65 papers
Deep Sigma Point Processes for RCS Modeling in Spaceborne SAR Imagery
Khalid El-Darymli, Christoph H. Gierull, Katerina Biron +1
Radar cross-section (RCS) modeling is foundational to advancing the utility and sensitivity of spaceborne radar systems. This study introduces a deep sigma-point process (DSPP) mod…
WISDOM: An AI-powered framework for emerging research detection using weak signal analysis and advanced topic modeling
Ashkan Ebadi, Alain Auger, Yvan Gauthier
The landscape of science and technology is characterized by its dynamic and evolving nature, constantly reshaped by new discoveries, innovations, and paradigm shifts. Moreover, sci…
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Exploration is a significant challenge in practical reinforcement learning (RL), and uncertainty-aware exploration that incorporates the quantification of epistemic and aleatory un…
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Sample efficiency is central to developing practical reinforcement learning (RL) for complex and large-scale decision-making problems. The ability to transfer and generalize knowle…
Non-negative Matrix Factorization using Partial Prior Knowledge for Radiation Dosimetry
Boby Lessard, Frédéric Marcotte, Arthur Lalonde +4
Hyperspectral unmixing aims at decomposing a given signal into its spectral signatures and its associated fractional abundances. To improve the accuracy of this decomposition, algo…
Off the Beaten Track: Laterally Weighted Motion Planning for Local Obstacle Avoidance
Jordy Sehn, Timothy D. Barfoot, Jack Collier
We extend the behaviour of generic sample-based motion planners to support obstacle avoidance during long-range path following by introducing a new edge-cost metric paired with a c…