Pierrick Pochelu

According to our database, Pierrick Pochelu authored at least 10 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

SerializableSimpy: Parallel and Serializable Discrete-Event Simulation in Python.

Pierrick Pochelu

J. Open Source Softw., February, 2026

What artificial intelligence can do for high-performance computing systems?

Pierrick Pochelu, Hyacinthe Cartiaux, Julien Schleich

Eng. Appl. Artif. Intell., 2026

2024

Mastering Computer Vision Inference Frameworks.

Pierrick Pochelu, Oscar Castro-López

Proceedings of the Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

JaxDecompiler: Redefining Gradient-Informed Software Design.

Pierrick Pochelu

Proceedings of the Optimization and Learning - 7th International Conference, 2024

2022

Ensembles of Deep Neural Networks distributed and parallel for the energy industry. (Ensembles de réseaux de neurones répartis et parallèles appliqués au domaine de l'énergie).

Pierrick Pochelu

PhD thesis, 2022

Deep Learning Inference Frameworks Benchmark.

Pierrick Pochelu

CoRR, 2022

Weakly Supervised Faster-RCNN+FPN to classify animals in camera trap images.

Pierrick Pochelu, Clara Erard, Philippe Cordier, Serge G. Petiton, Bruno Conche

Proceedings of the IVSP 2022: 4th International Conference on Image, Video and Signal Processing, Singapore, March 18, 2022

A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters.

Pierrick Pochelu, Serge G. Petiton, Bruno Conche

Proceedings of the HPC Asia 2022: International Conference on High Performance Computing in Asia-Pacific Region, Virtual Event, Japan, January 12, 2022

Distributed Ensembles of Reinforcement Learning Agents for Electricity Control.

Pierrick Pochelu, Bruno Conche, Serge G. Petiton

Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2022

2021

An efficient and flexible inference system for serving heterogeneous ensembles of deep neural networks.

Pierrick Pochelu, Serge G. Petiton, Bruno Conche

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021