DR MAURIZIO FILIPPONE
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AXA Chair of Computational Statistics and Assistant Professor at EURECOM

Address:
Campus SophiaTech
450 Route des Chappes
06410 Biot, FRANCE

Office: 419

Phone: +33 4 93 00 81 35

Email Address: maurizio.filippone [at] eurecom.fr

Book time with me on: youcanbook.me



Word cloud research


NEWS

17-08-17  Check out our new paper "Pseudo-extended Markov chain Monte Carlo" joint work with C. Nemeth, F. Lindsten and J. Hensman (link)

22-06-17  The paper "Entropic Trace Estimates for Log Determinants" has been accepted at ECML 2017! (link)

12-06-17  The paper "Bayesian Inference of Log Determinants" has been accepted at UAI 2017! (link)

12-06-17  The paper "AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models" has been accepted at UAI 2017! (link)

17-05-17  Talk at the AXA Data Innovation Lab - Paris, France: "Bayesian Inference: Challenges from Modern Applications"

13-05-17  The paper "Random Feature Expansions for Deep Gaussian Processes" has been accepted at ICML 2017! (link) (pdf) (code)

10-05-17  Talk at the OQUAIDO scientific meeting at the University of Nice, France: "Unbiased computations for tractable and scalable learning of Gaussian processes"

03-05-17  Post-Doc and PhD positions available in my group (Post-Doc announcement) (Ph.D. announcement)

25-04-17  Check out our new paper "Entropic Trace Estimates for Log Determinants" joint work with J. Fitzsimons, D. Granziol, K. Cutajar, M. Osborne, and S. Roberts (link)

24-04-17  Talk at the École Centrale de Lille, France: "Unbiased computations for tractable and scalable learning of Gaussian processes"

14-04-17  Talk at Yandex, Moscow: "Practical and Scalable Inference for Deep Gaussian Processes" (slides)

06-04-17  Check out our new paper "Bayesian Inference of Log Determinants" joint work with J. Fitzsimons, K. Cutajar, M. Osborne, and S. Roberts (link)

29-03-17  Talk at Google Research, NYC: "Unbiased computations for tractable and scalable learning of Gaussian processes"

23-03-17  Talk at the Mascot Num 2017 Meeting: "Practical and Scalable Inference for Deep Gaussian Processes" (slides)

04-02-17  The paper "Mini-Batch Spectral Clustering" has been accepted at IJCNN 2017! (pdf) (code)

08-01-17  Check out our new paper "Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation" joint work with M. Lorenzi, D. C. Alexander, S. Ourselin (link)

05-01-17  The paper "Adaptive Multiple Importance Sampling for Gaussian Processes" has been accepted for publication in the Journal of Statistical Computation and Simulation!

15-11-16  The paper "Accelerating Deep Gaussian Processes Inference with Arc-Cosine Kernels" has been accepted at the Bayesian Deep Learning Workshop at NIPS 2016! (pdf) (link)

25-10-16  Fully funded PhD scholarship in Bayesian nonparametrics (link)

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