Operational semantics of Standard Prolog: an axiomatic approach. - Jean-Paul Delahaye; François Denis (SPLT, 1990)

Unfolding, Procedural and Fixpoint Semantics of Logic Programs. - François Denis; Jean-Paul Delahaye (STACS, 1991)

Is there an Axiomatic Semantics for Standard Pure Prolog. - François Denis; Jean-Paul Delahaye (Theor. Comput. Sci., 1991)

PAC Learning with Simple Examples. - François Denis; Cyrille D'Halluin; Rémi Gilleron (STACS, 1996)

PAC Learning from Positive Statistical Queries. - François Denis (ALT, 1998)

Positive and Unlabeled Examples Help Learning. - Francesco De Comité; François Denis; Rémi Gilleron; Fabien Letouzey (ALT, 1999)

Finding a Minimal 1-DNF Consistent with a Positive Sample is LOGSNP-Complete. - François Denis (Inf. Process. Lett., 1999)

Learning Regular Languages Using Non Deterministic Finite Automata. - François Denis; Aurélien Lemay; Alain Terlutte (ICGI, 2000)

Learning Regular Languages Using RFSA. - François Denis; Aurélien Lemay; Alain Terlutte (ALT, 2001)

PAC Learning under Helpful Distributions. - François Denis; Rémi Gilleron (RAIRO Theor. Informatics Appl., 2001)

Learning Regular Languages from Simple Positive Examples. - François Denis (Mach. Learn., 2001)

Some Classes of Regular Languages Identifiable in the Limit from Positive Data. - François Denis; Aurélien Lemay; Alain Terlutte (ICGI, 2002)

Learning Probabilistic Residual Finite State Automata. - Yann Esposito; Aurélien Lemay; François Denis; Pierre Dupont (ICGI, 2002)

Residual Finite State Automata. - François Denis; Aurélien Lemay; Alain Terlutte (Fundam. Informaticae, 2002)

Residual Languages and Probabilistic Automata. - François Denis; Yann Esposito (ICALP, 2003)

On the consistency of the minimum evolution principle of phylogenetic inference. - François Denis; Olivier Gascuel (Discret. Appl. Math., 2003)

Learning Classes of Probabilistic Automata. - François Denis; Yann Esposito (COLT, 2004)

Learning regular languages using RFSAs. - François Denis; Aurélien Lemay; Alain Terlutte (Theor. Comput. Sci., 2004)

Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms. - Pierre Dupont; François Denis; Yann Esposito (Pattern Recognit., 2005)

Learning from positive and unlabeled examples. - François Denis; Rémi Gilleron; Fabien Letouzey (Theor. Comput. Sci., 2005)

Learning Rational Stochastic Languages. - François Denis; Yann Esposito; Amaury Habrard (COLT, 2006)

Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference. - Amaury Habrard; François Denis; Yann Esposito (ICGI, 2006)

Efficient learning of Naive Bayes classifiers under class-conditional classification noise. - François Denis; Christophe Nicolas Magnan; Liva Ralaivola (ICML, 2006)

CN = CPCN. - Liva Ralaivola; François Denis; Christophe Nicolas Magnan (ICML, 2006)

Learning Rational Stochastic Tree Languages. - François Denis; Amaury Habrard (ALT, 2007)

A Protocol to Detect Local Affinities Involved in Proteins Distant Interactions. - Christophe Nicolas Magnan; Cécile Capponi; François Denis (BIBM, 2007)

Relevant Representations for the Inference of Rational Stochastic Tree Languages. - François Denis; Édouard Gilbert; Amaury Habrard; Faissal Ouardi; Marc Tommasi (ICGI, 2008)

On Probability Distributions for Trees: Representations, Inference and Learning - François Denis; Amaury Habrard; Rémi Gilleron; Marc Tommasi; Édouard Gilbert (CoRR, 2008)

On Rational Stochastic Languages. - François Denis; Yann Esposito (Fundam. Informaticae, 2008)

Grammatical inference as a principal component analysis problem. - Raphaël Bailly; François Denis; Liva Ralaivola (ICML, 2009)

A Spectral Approach for Probabilistic Grammatical Inference on Trees. - Raphaël Bailly; Amaury Habrard; François Denis (ALT, 2010)

Absolute convergence of rational series is semi-decidable. - Raphaël Bailly; François Denis (Inf. Comput., 2011)

Some improvements of the spectral learning approach for probabilistic grammatical inference. - Mattias Gybels; François Denis; Amaury Habrard (ICGI, 2014)

Maximizing a Tree Series in the Representation Space. - Guillaume Rabusseau; François Denis (ICGI, 2014)

Learning Negative Mixture Models by Tensor Decompositions. - Guillaume Rabusseau; François Denis (CoRR, 2014)

Recognizable Series on Hypergraphs. - Raphaël Bailly; François Denis; Guillaume Rabusseau (LATA, 2015)

Sp2Learn: A Toolbox for the Spectral Learning of Weighted Automata. - Denis Arrivault; Dominique Benielli; François Denis; Rémi Eyraud (ICGI, 2016)

Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. - François Denis; Mattias Gybels; Amaury Habrard (J. Mach. Learn. Res., 2016)

Recognizable series on graphs and hypergraphs. - Raphaël Bailly; Guillaume Rabusseau; François Denis (J. Comput. Syst. Sci., 2019)