output
20032024
most citedThe NANOGrav 15-year Data Set: Constraints on Supermassive Black Hole Binaries from the Gravitational Wave Background

380 citations

Showing 2021Show all

26 papers · 1 filter

math.OC2021

Robust reliability-based topology optimization under random-field material model

Trung Pham, Christopher Hoyle

This paper proposes an algorithm to find robust reliability-based topology optimized designs under a random-field material model. The initial design domain is made of linear elasti…

math.OC20212 cited

Reliability-based topology optimization under random-field material model

Trung Pham, Christopher Hoyle

This paper presents an algorithm for reliability-based topology optimization of linear elastic continua under random-field material model. The modelling random field is discretized…

astro-ph.HE2021

Host galaxies and electromagnetic counterparts to binary neutron star mergers across the cosmic time: Detectability of GW170817-like events

Rosalba Perna, M. Celeste Artale, Yi-Han Wang +4

The detection of electromagnetic radiation (EM) accompanying the gravitational wave (GW) signal from the binary neutron star (BNS) merger GW170817 has revealed that these systems c…

cs.CL2021

Text Counterfactuals via Latent Optimization and Shapley-Guided Search

Quintin Pope, Xiaoli Z. Fern

We study the problem of generating counterfactual text for a classifier as a means for understanding and debugging classification. Given a textual input and a classification model,…

cs.RO20217 cited

Optimal Sequential Stochastic Deployment of Multiple Passenger Robots

Chris, Lee, Graeme Best +1

We present a new algorithm for deploying passenger robots in marsupial robot systems. A marsupial robot system consists of a carrier robot (e.g., a ground vehicle), which is highly…

cs.AI2021

Dynamic probabilistic logic models for effective abstractions in RL

Harsha Kokel, Arjun Manoharan, Sriraam Natarajan +2

State abstraction enables sample-efficient learning and better task transfer in complex reinforcement learning environments. Recently, we proposed RePReL (Kokel et al. 2021), a hie…