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ORCIDJérémy Charlier
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2020 – today
- 2023
[j2]Zeinab Sherkatghanad, Moloud Abdar, Jérémy Charlier, Vladimir Makarenkov
:
Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review. Briefings Bioinform. 24(3) (2023)- 2021
- [j1]Jérémy Charlier, Robert Nadon, Vladimir Makarenkov:
Accurate deep learning off-target prediction with novel sgRNA-DNA sequence encoding in CRISPR-Cas9 gene editing. Bioinform. 37(16): 2299-2307 (2021) - 2020
- [c8]Jérémy Charlier, Vladimir Makarenkov:
VecHGrad for Solving Accurately Tensor Decomposition. Canadian AI 2020: 125-137 - [i11]Jérémy Charlier, Vladimir Makarenkov:
XtracTree for Regulator Validation of Bagging Methods Used in Retail Banking. CoRR abs/2004.02326 (2020)
2010 – 2019
- 2019
- [c7]Jérémy Charlier, Radu State, Jean Hilger:
Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment. Canadian AI 2019: 556-562 - [c6]Jérémy Charlier, Gaston Ormazabal, Radu State, Jean Hilger:
MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning. MIDAS@PKDD 2019: 1-15 - [c5]Jérémy Charlier, Radu State, Jean Hilger:
PHom-GeM: Persistent Homology for Generative Models. SDS 2019: 87-92 - [i10]Jérémy Charlier, Radu State, Jean Hilger:
Modeling Smart Contracts Activities: A Tensor Based Approach. CoRR abs/1905.09868 (2019) - [i9]Jérémy Charlier, Radu State, Jean Hilger:
Non-Negative PARATUCK2 Tensor Decomposition Combined to LSTM Network For Smart Contracts Profiling. CoRR abs/1905.09869 (2019) - [i8]Jérémy Charlier, Radu State, Jean Hilger:
PHom-GeM: Persistent Homology for Generative Models. CoRR abs/1905.09894 (2019) - [i7]Jérémy Charlier, Eric Falk, Radu State, Jean Hilger:
User-Device Authentication in Mobile Banking using APHEN for Paratuck2 Tensor Decomposition. CoRR abs/1905.10363 (2019) - [i6]Jérémy Charlier, Gaston Ormazabal, Radu State, Jean Hilger:
VecHGrad for solving accurately complex tensor decomposition. CoRR abs/1905.12413 (2019) - [i5]Jérémy Charlier, Gaston Ormazabal, Radu State, Jean Hilger:
MQLV: Modified Q-Learning for Vasicek Model. CoRR abs/1905.12567 (2019) - [i4]Jérémy Charlier, Radu State, Jean Hilger:
Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment. CoRR abs/1905.12568 (2019) - [i3]Jérémy Charlier, François Petit, Gaston Ormazabal, Radu State, Jean Hilger:
PHom-WAE: Persitent Homology for Wasserstein Auto-Encoders. CoRR abs/1905.13020 (2019) - [i2]Jérémy Charlier, Aman Singh, Gaston Ormazabal, Radu State, Henning Schulzrinne:
SynGAN: Towards Generating Synthetic Network Attacks using GANs. CoRR abs/1908.09899 (2019) - [i1]Jérémy Charlier:
From Persistent Homology to Reinforcement Learning with Applications for Retail Banking. CoRR abs/1911.11573 (2019) - 2018
- [c4]Jérémy Charlier, Radu State, Jean Hilger:
Non-negative Paratuck2 Tensor Decomposition Combined to LSTM Network for Smart Contracts Profiling. BigComp 2018: 74-81 - [c3]Jérémy Charlier, Eric Falk, Radu State, Jean Hilger:
User-Device Authentication in Mobile Banking Using APHEN for Paratuck2 Tensor Decomposition. ICDM Workshops 2018: 886-894 - 2017
- [c2]Eric Falk, Jérémy Charlier, Radu State:
Your Moves, Your Device: Establishing Behavior Profiles Using Tensors. ADMA 2017: 460-474 - [c1]Jérémy Charlier, Sofiane Lagraa, Radu State, Jérôme François:
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining. MIDAS@PKDD/ECML 2017: 31-42
Coauthor Index
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