74 citations
- The University of TokyoJP3 papers
- ETH ZurichCH2 papers
- Hiroshima City UniversityJP2 papers
- Laboratoire d'Informatique Fondamentale et Appliquée de ToursFR2 papers
- Stanford UniversityUS2 papers
- Tokyo Institute of TechnologyJP2 papers
- Aalto UniversityFI1 paper
- Advanced Science Research CenterJP1 paper
- Applied Photonics (United Kingdom)GB1 paper
- ARC Centre of Excellence for Transformative Meta-Optical SystemsAU1 paper
- Australian National UniversityAU1 paper
- Barcelona Institute of Science and TechnologyES1 paper
8 papers
Challenges of Explainability in Continual Learning for Time Series Forecasting
Quentin Besnard, Emmanuel Doumard, Nicolas Labroche +2
Deep learning models have shown strong potential for time series forecasting, yet their deployment in real-world environmental monitoring remains challenging due to non-stationary…
Learning a Distance for the Clustering of Patients with Amyotrophic Lateral Sclerosis
Guillaume Tejedor, Veronika Peralta, Nicolas Labroche +3
Amyotrophic lateral sclerosis (ALS) is a severe disease with a typical survival of 3-5 years after symptom onset. Current treatments offer only limited life extension, and the vari…
EdgeCodec: Onboard Lightweight High Fidelity Neural Compressor with Residual Vector Quantization
Benjamin Hodo, Tommaso Polonelli, Amirhossein Moallemi +2
We present EdgeCodec, an end-to-end neural compressor for barometric data collected from wind turbine blades. EdgeCodec leverages a heavily asymmetric autoencoder architecture, tra…
Roadmap for Photonics with 2D Materials
F. Javier García de Abajo, D. N. Basov, Frank H. L. Koppens +145
Triggered by the development of exfoliation and the identification of a wide range of extraordinary physical properties in self-standing films consisting of one or few atomic layer…
Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine
Toru Aonishi, Tatsuya Nagasawa, Toshiyuki Koizumi +5
In recent years, quantum Ising machines have drawn a lot of attention, but due to physical implementation constraints, it has been difficult to achieve dense coupling, such as full…
Noise Balance and Stationary Distribution of Stochastic Gradient Descent
Liu Ziyin, Hongchao Li, Masahito Ueda
The stochastic gradient descent (SGD) algorithm is the algorithm we use to train neural networks. However, it remains poorly understood how the SGD navigates the highly nonlinear a…