Frédéric Odermatt

According to our database, Frédéric Odermatt authored at least 5 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting.

Young-Jin Park, Donghyun Kim, Frédéric Odermatt, Juho Lee, Kyung-Min Kim

CoRR, 2024

2023

Gradient descent-based programming of analog in-memory computing cores.

Julian Büchel, Athanasios Vasilopoulos, Benedikt Kersting, Frédéric Odermatt, Kevin Brew, Injo Ok, Samuel Choi, Iqbal Saraf, Victor Chan, Timothy Philip, Nicole Saulnier, Vijay Narayanan, Manuel Le Gallo, Abu Sebastian

CoRR, 2023

Cascaded Beam Search: Plug-and-Play Terminology-Forcing For Neural Machine Translation.

Frédéric Odermatt, Béni Egressy, Roger Wattenhofer

CoRR, 2023

Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators.

Malte J. Rasch, Charles Mackin, Manuel Le Gallo, An Chen, Andrea Fasoli, Frédéric Odermatt, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan

CoRR, 2023

2022

A Large-Scale Ensemble Learning Framework for Demand Forecasting.

Young-Jin Park, Donghyun Kim, Frédéric Odermatt, Juho Lee, Kyung-Min Kim

Proceedings of the IEEE International Conference on Data Mining, 2022