no code implementations • 18 Sep 2023 • Kaya Kuru, John Michael Pinder, Benjamin Jon Watkinson, Darren Ansell, Keith Vinning, Lee Moore, Chris Gilbert, Aadithya Sujit, David Jones
For drones, as safety-critical systems, there is an increasing need for onboard detect & avoid (DAA) technology i) to see, sense or detect conflicting traffic or imminent non-cooperative threats due to their high mobility with multiple degrees of freedom and the complexity of deployed unstructured environments, and subsequently ii) to take the appropriate actions to avoid collisions depending upon the level of autonomy.
no code implementations • 1 Jun 2023 • Evan Munro, David Jones, Jennifer Brennan, Roland Nelet, Vahab Mirrokni, Jean Pouget-Abadie
In online platforms, the impact of a treatment on an observed outcome may change over time as 1) users learn about the intervention, and 2) the system personalization, such as individualized recommendations, change over time.
no code implementations • 13 Sep 2022 • Alzayat Saleh, David Jones, Dean Jerry, Mostafa Rahimi Azghadi
Transformer-based models, such as the Vision Transformer (ViT), can outperform onvolutional Neural Networks (CNNs) in some vision tasks when there is sufficient training data.
no code implementations • 30 Jun 2021 • Nikhil Muralidhar, Sathappah Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays 'Skip' McCormick, Naren Ramakrishnan
We describe lessons learned from developing and deploying machine learning models at scale across the enterprise in a range of financial analytics applications.
no code implementations • 21 May 2021 • Ric Real, James Gopsill, David Jones, Chris Snider, Ben Hicks
Prior work has shown Convolutional Neural Networks (CNNs) trained on surrogate Computer Aided Design (CAD) models are able to detect and classify real-world artefacts from photographs.
no code implementations • 4 May 2021 • David Jones, Nathan Jacobs
We show that our method performs as well as the best baseline in areas with similar intensity distributions, and outperforms all baselines in areas with different intensity distributions.
1 code implementation • 30 Jun 2020 • Kyle E Conroy, Angela Kochoska, Daniel Hey, Herbert Pablo, Kelly M Hambleton, David Jones, Joseph Giammarco, Michael Abdul-Masih, Andrej Prsa
The inverse problem, obtaining orbital and stellar parameters given observational data, is more complicated and computationally expensive as it requires generating a large set of forward-models to determine which set of parameters and uncertainties best represent the available observational data.
Solar and Stellar Astrophysics Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics
no code implementations • LREC 2020 • Georg Rehm, Maria Berger, Ela Elsholz, Stefanie Hegele, Florian Kintzel, Katrin Marheinecke, Stelios Piperidis, Miltos Deligiannis, Dimitris Galanis, Katerina Gkirtzou, Penny Labropoulou, Kalina Bontcheva, David Jones, Ian Roberts, Jan Hajic, Jana Hamrlová, Lukáš Kačena, Khalid Choukri, Victoria Arranz, Andrejs Vasiļjevs, Orians Anvari, Andis Lagzdiņš, Jūlija Meļņika, Gerhard Backfried, Erinç Dikici, Miroslav Janosik, Katja Prinz, Christoph Prinz, Severin Stampler, Dorothea Thomas-Aniola, José Manuel Gómez Pérez, Andres Garcia Silva, Christian Berrío, Ulrich Germann, Steve Renals, Ondrej Klejch
With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs).
no code implementations • 6 Mar 2019 • David Jones, Anja Schroeder, Geoff Nitschke
The Zone of Avoidance makes it difficult for astronomers to catalogue galaxies at low latitudes to our galactic plane due to high star densities and extinction.