Philippe Very - RankMe

20 papers A* 1C 1Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Neural ODE Approach to Aircraft Flight Dynamics Modelling. CoRR Gabriel Jarry, Ramon Dalmau, Xavier Olive, Philippe Very
2025	J	`jnl`	Aircraft Fuel Flow Modelling with Ageing Effects: From Parametric Corrections to Neural Networks. CoRR Gabriel Jarry, Ramon Dalmau, Philippe Very, Junzi Sun
2025	J	`jnl`	Contrail-to-Flight Attribution Using Ground Visible Cameras and Flight Surveillance Data. CoRR Ramon Dalmau, Gabriel Jarry, Philippe Very
2025	J	`jnl`	GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences. CoRR Gabriel Jarry, Ramon Dalmau, Philippe Very, Franck Ballerini, Stefania-Denisa Bocu
2024	J	`jnl`	On the Detection of Aircraft Single Engine Taxi using Deep Learning Models. CoRR Gabriel Jarry, Philippe Very, Ramon Dalmau, Daniel Delahaye, Arthur Houdant
2024	J	`jnl`	On the Generalization Properties of Deep Learning for Aircraft Fuel Flow Estimation Models. CoRR Gabriel Jarry, Ramon Dalmau, Philippe Very, Junzi Sun
2021	A*	`conf`	Robust Domain Adaptation: Representations, Weights and Inductive Bias (Extended Abstract). IJCAI Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
2021	—	`conf`	Stochastic Adversarial Gradient Embedding for Active Domain Adaptation. IAL@PKDD/ECML Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
2020	—	`conf`	Robust Domain Adaptation: Representations, Weights and Inductive Bias. ECML/PKDD (1) Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
2020	J	`jnl`	Robust Domain Adaptation: Representations, Weights and Inductive Bias. CoRR Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
2020	J	`jnl`	Stochastic Adversarial Gradient Embedding for Active Domain Adaptation. CoRR Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
2019	J	`jnl`	Hidden Covariate Shift: A Minimal Assumption For Domain Adaptation. CoRR Victor Bouvier, Philippe Very, Céline Hudelot, Clément Chastagnol
2019	J	`jnl`	Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets. CoRR Victor Bouvier, Philippe Very, Céline Hudelot, Clément Chastagnol
2016	J	`jnl`	Toward a generic representation of random variables for machine learning. Pattern Recognit. Lett. Philippe Donnat, Gautier Marti, Philippe Very
2015	C	`conf`	A Proposal of a Methodological Framework with Experimental Guidelines to Investigate Clustering Stability on Financial Time Series. ICMLA Gautier Marti, Philippe Very, Philippe Donnat, Frank Nielsen
2015	J	`jnl`	A proposal of a methodological framework with experimental guidelines to investigate clustering stability on financial time series. CoRR Gautier Marti, Philippe Very, Philippe Donnat, Frank Nielsen
2015	—	`conf`	Clustering Random Walk Time Series. GSI Gautier Marti, Frank Nielsen, Philippe Very, Philippe Donnat
2015	J	`jnl`	Comment partitionner automatiquement des marches aléatoires ? Avec application à la finance quantitative. CoRR Gautier Marti, Frank Nielsen, Philippe Very, Philippe Donnat
2015	J	`jnl`	HCMapper: An interactive visualization tool to compare partition-based flat clustering extracted from pairs of dendrograms. CoRR Gautier Marti, Philippe Donnat, Frank Nielsen, Philippe Very
2015	J	`jnl`	Toward a generic representation of random variables for machine learning. CoRR Gautier Marti, Philippe Very, Philippe Donnat