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2020 – today
- 2023
[c119]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. ALT 2023: 447-470- [i68]Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris C. Holmes:
Causal Falsification of Digital Twins. CoRR abs/2301.07210 (2023) - [i67]Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts:
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. CoRR abs/2301.08187 (2023) - [i66]Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola:
SE(3) diffusion model with application to protein backbone generation. CoRR abs/2302.02277 (2023) - [i65]Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl:
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR abs/2302.11552 (2023) - [i64]Francisco Vargas, Will Grathwohl, Arnaud Doucet:
Denoising Diffusion Samplers. CoRR abs/2302.13834 (2023) - [i63]Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet:
Diffusion Schrödinger Bridge Matching. CoRR abs/2303.16852 (2023) - 2022
- [j65]Maxime Vono, Daniel Paulin, Arnaud Doucet:
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting. J. Mach. Learn. Res. 23: 25:1-25:69 (2022) - [j64]Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet:
COIN++: Neural Compression Across Modalities. Trans. Mach. Learn. Res. 2022 (2022) - [j63]Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet:
An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. 2022 (2022) - [c118]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Conditionally Gaussian PAC-Bayes. AISTATS 2022: 2311-2329 - [c117]Emilien Dupont, Yee Whye Teh, Arnaud Doucet:
Generative Models as Distributions of Functions. AISTATS 2022: 2989-3015 - [c116]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. AISTATS 2022: 3066-3079 - [c115]Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Chained generalisation bounds. COLT 2022: 4212-4257 - [c114]Angad Singh, Omar Makhlouf, Maximilian Igl, João Messias, Arnaud Doucet, Shimon Whiteson:
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRL 2022: 1168-1177 - [c113]David Stutz
, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet:
Learning Optimal Conformal Classifiers. ICLR 2022 - [c112]Alexander G. de G. Matthews, Michael Arbel, Danilo Jimenez Rezende, Arnaud Doucet:
Continual Repeated Annealed Flow Transport Monte Carlo. ICML 2022: 15196-15219 - [c111]Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton:
Importance Weighted Kernel Bayes' Rule. ICML 2022: 24524-24538 - [c110]Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modelling. NeurIPS 2022 - [c109]Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet:
A Continuous Time Framework for Discrete Denoising Models. NeurIPS 2022 - [c108]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022 - [c107]Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann:
Score-Based Diffusion meets Annealed Importance Sampling. NeurIPS 2022 - [c106]Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts:
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS 2022 - [c105]Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. NeurIPS 2022 - [c104]Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Mitigating statistical bias within differentially private synthetic data. UAI 2022: 696-705 - [c103]Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Conditional simulation using diffusion Schrödinger bridges. UAI 2022: 1792-1802 - [i62]Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet:
COIN++: Data Agnostic Neural Compression. CoRR abs/2201.12904 (2022) - [i61]Alexander G. de G. Matthews, Michael Arbel, Danilo J. Rezende, Arnaud Doucet:
Continual Repeated Annealed Flow Transport Monte Carlo. CoRR abs/2201.13117 (2022) - [i60]Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton:
Importance Weighting Approach in Kernel Bayes' Rule. CoRR abs/2202.02474 (2022) - [i59]Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modeling. CoRR abs/2202.02763 (2022) - [i58]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. CoRR abs/2202.11455 (2022) - [i57]Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Conditional Simulation Using Diffusion Schrödinger Bridges. CoRR abs/2202.13460 (2022) - [i56]Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Chained Generalisation Bounds. CoRR abs/2203.00977 (2022) - [i55]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR abs/2205.13320 (2022) - [i54]Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet:
A Continuous Time Framework for Discrete Denoising Models. CoRR abs/2205.14987 (2022) - [i53]Muhammad Faaiz Taufiq, Jean-Francois Ton, Robert Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. CoRR abs/2206.04405 (2022) - [i52]Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Ranking in Contextual Multi-Armed Bandits. CoRR abs/2207.00109 (2022) - [i51]Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet:
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR abs/2207.02099 (2022) - [i50]James Thornton, Michael Hutchinson, Emile Mathieu, Valentin De Bortoli, Yee Whye Teh, Arnaud Doucet:
Riemannian Diffusion Schrödinger Bridge. CoRR abs/2207.03024 (2022) - [i49]Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann:
Score-Based Diffusion meets Annealed Importance Sampling. CoRR abs/2208.07698 (2022) - [i48]Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet:
A PAC-Bayes bound for deterministic classifiers. CoRR abs/2209.02525 (2022) - [i47]Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen:
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows. CoRR abs/2209.09936 (2022) - [i46]Angus Phillips, Thomas Seror, Michael Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu:
Spectral Diffusion Processes. CoRR abs/2209.14125 (2022) - [i45]Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet:
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. CoRR abs/2210.06226 (2022) - [i44]Pierre Glaser, Michael Arbel, Arnaud Doucet, Arthur Gretton:
Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference. CoRR abs/2210.14756 (2022) - [i43]Pierre H. Richemond, Sander Dieleman, Arnaud Doucet:
Categorical SDEs with Simplex Diffusion. CoRR abs/2210.14784 (2022) - [i42]Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
From Denoising Diffusions to Denoising Markov Models. CoRR abs/2211.03595 (2022) - [i41]Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler:
Continuous diffusion for categorical data. CoRR abs/2211.15089 (2022) - [i40]Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson:
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRR abs/2212.06968 (2022) - 2021
- [j62]Philippe Gagnon, Arnaud Doucet:
Nonreversible Jump Algorithms for Bayesian Nested Model Selection. J. Comput. Graph. Stat. 30(2): 312-323 (2021) - [j61]Vladislav Z. B. Tadic, Arnaud Doucet:
Bias of Particle Approximations to Optimal Filter Derivative. SIAM J. Control. Optim. 59(1): 727-748 (2021) - [j60]Adrian N. Bishop, Arnaud Doucet:
Network Consensus in the Wasserstein Metric Space of Probability Measures. SIAM J. Control. Optim. 59(5): 3261-3277 (2021) - [j59]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Arnaud Doucet:
Dual Space Preconditioning for Gradient Descent. SIAM J. Optim. 31(1): 991-1016 (2021) - [j58]Vladislav Z. B. Tadic, Arnaud Doucet:
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation. IEEE Trans. Inf. Theory 67(3): 1825-1848 (2021) - [c102]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. AISTATS 2021: 1324-1332 - [c101]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
The Curse of Depth in Kernel Regime. ICBINB@NeurIPS 2021: 41-47 - [c100]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Robust Pruning at Initialization. ICLR 2021 - [c99]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. ICLR 2021 - [c98]Michael Arbel, Alexander G. de G. Matthews, Arnaud Doucet:
Annealed Flow Transport Monte Carlo. ICML 2021: 318-330 - [c97]Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet:
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. ICML 2021: 2100-2111 - [c96]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML 2021: 9136-9147 - [c95]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. ICML 2021: 10247-10257 - [c94]Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X. Robert:
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. NeurIPS 2021: 17060-17071 - [c93]Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet:
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. NeurIPS 2021: 17695-17709 - [c92]Andrew Campbell, Yuyang Shi, Thomas Rainforth, Arnaud Doucet:
Online Variational Filtering and Parameter Learning. NeurIPS 2021: 18633-18645 - [c91]Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet:
Variational inference with continuously-indexed normalizing flows. UAI 2021: 44-53 - [c90]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. UAI 2021: 707-717 - [i39]Emilien Dupont, Yee Whye Teh, Arnaud Doucet:
Generative Models as Distributions of Functions. CoRR abs/2102.04776 (2021) - [i38]Michael Arbel, Alexander G. de G. Matthews, Arnaud Doucet:
Annealed Flow Transport Monte Carlo. CoRR abs/2102.07501 (2021) - [i37]Adrien Corenflos, James Thornton, Arnaud Doucet, George Deligiannidis:
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. CoRR abs/2102.07850 (2021) - [i36]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR abs/2102.11086 (2021) - [i35]Emilien Dupont, Adam Golinski, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet:
COIN: COmpression with Implicit Neural representations. CoRR abs/2103.03123 (2021) - [i34]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR abs/2105.10148 (2021) - [i33]Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet:
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. CoRR abs/2106.01357 (2021) - [i32]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. CoRR abs/2106.09798 (2021) - [i31]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. CoRR abs/2106.15921 (2021) - [i30]George Deligiannidis, Valentin De Bortoli, Arnaud Doucet:
Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure. CoRR abs/2108.08129 (2021) - [i29]Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR abs/2108.10934 (2021) - [i28]David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet:
Learning Optimal Conformal Classifiers. CoRR abs/2110.09192 (2021) - [i27]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Conditional Gaussian PAC-Bayes. CoRR abs/2110.11886 (2021) - [i26]Andrew Campbell, Yuyang Shi, Tom Rainforth, Arnaud Doucet:
Online Variational Filtering and Parameter Learning. CoRR abs/2110.13549 (2021) - [i25]Valentin De Bortoli, Arnaud Doucet, Jeremy Heng, James Thornton:
Simulating Diffusion Bridges with Score Matching. CoRR abs/2111.07243 (2021) - 2020
- [c89]Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet:
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows. ICML 2020: 2133-2143 - [c88]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas:
Modular Meta-Learning with Shrinkage. NeurIPS 2020 - [i24]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Pruning untrained neural networks: Principles and Analysis. CoRR abs/2002.08797 (2020) - [i23]Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet:
Variational Inference with Continuously-Indexed Normalizing Flows. CoRR abs/2007.05426 (2020) - [i22]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains. CoRR abs/2010.01845 (2020) - [i21]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. CoRR abs/2010.07154 (2020) - [i20]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. CoRR abs/2010.12859 (2020)
2010 – 2019
- 2019
- [j57]Vladislav Z. B. Tadic, Arnaud Doucet:
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models. IEEE Trans. Inf. Theory 65(12): 7950-7975 (2019) - [c87]Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis:
Bernoulli Race Particle Filters. AISTATS 2019: 2350-2358 - [c86]Lawrece Middleton, George Deligiannidis, Arnaud Doucet, Pierre E. Jacob:
Unbiased Smoothing using Particle Independent Metropolis-Hastings. AISTATS 2019: 2378-2387 - [c85]Vladislav Z. B. Tadic, Arnaud Doucet:
Stability of Optimal Filter Higher-Order Derivatives. CDC 2019: 1644-1649 - [c84]Robert Cornish, Paul Vanetti, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet:
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. ICML 2019: 1351-1360 - [c83]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Impact of the Activation function on Deep Neural Networks Training. ICML 2019: 2672-2680 - [c82]Alex Shestopaloff, Arnaud Doucet:
Replica Conditional Sequential Monte Carlo. ICML 2019: 5749-5757 - [c81]Vladislav Z. B. Tadic, Arnaud Doucet:
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation. ISIT 2019: 887-891 - [c80]Emilien Dupont, Arnaud Doucet, Yee Whye Teh:
Augmented Neural ODEs. NeurIPS 2019: 3134-3144 - [i19]Robert Cornish, Paul Vanetti, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet:
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. CoRR abs/1901.09881 (2019) - [i18]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Impact of the Activation Function on Deep Neural Networks Training. CoRR abs/1902.06853 (2019) - [i17]Emilien Dupont, Arnaud Doucet, Yee Whye Teh:
Augmented Neural ODEs. CoRR abs/1904.01681 (2019) - [i16]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel. CoRR abs/1905.13654 (2019) - [i15]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas:
Modular Meta-Learning with Shrinkage. CoRR abs/1909.05557 (2019) - [i14]Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet:
Localised Generative Flows. CoRR abs/1909.13833 (2019) - 2018
- [c79]Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic:
Hamiltonian Variational Auto-Encoder. NeurIPS 2018: 8178-8188 - [i13]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Selection of Initialization and Activation Function for Deep Neural Networks. CoRR abs/1805.08266 (2018) - [i12]Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic:
Hamiltonian Variational Auto-Encoder. CoRR abs/1805.11328 (2018) - [i11]Vladislav Z. B. Tadic, Arnaud Doucet:
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models. CoRR abs/1806.09589 (2018) - [i10]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Brendan O'Donoghue, Arnaud Doucet:
Hamiltonian Descent Methods. CoRR abs/1809.05042 (2018) - 2017
- [j56]François Caron, Willie Neiswanger, Frank D. Wood, Arnaud Doucet, Manuel Davy:
Generalized Pólya Urn for Time-Varying Pitman-Yor Processes. J. Mach. Learn. Res. 18: 27:1-27:32 (2017) - [j55]Alexandre Bouchard-Côté, Arnaud Doucet, Andrew Roth:
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models. J. Mach. Learn. Res. 18: 28:1-28:39 (2017) - [j54]Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes:
On Markov chain Monte Carlo methods for tall data. J. Mach. Learn. Res. 18: 47:1-47:43 (2017) - [c78]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh:
Particle Value Functions. ICLR (Workshop) 2017 - [c77]Andrei-Cristian Barbos, Francois Caron, Jean-François Giovannelli, Arnaud Doucet:
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling. NIPS 2017: 5020-5028 - [c76]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh:
Filtering Variational Objectives. NIPS 2017: 6573-6583 - [i9]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh:
Particle Value Functions. CoRR abs/1703.05820 (2017) - [i8]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh:
Filtering Variational Objectives. CoRR abs/1705.09279 (2017) - 2016
- [c75]Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood:
Interacting Particle Markov Chain Monte Carlo. ICML 2016: 2616-2625 - 2015
- [j53]Pierre Del Moral, Arnaud Doucet, Sumeetpal S. Singh:
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative. SIAM J. Control. Optim. 53(3): 1278-1304 (2015) - [c74]Thibaut Liénart, Yee Whye Teh, Arnaud Doucet:
Expectation Particle Belief Propagation. NIPS 2015: 3609-3617 - [i7]Thibaut Liénart, Yee Whye Teh, Arnaud Doucet:
Expectation Particle Belief Propagation. CoRR abs/1506.05934 (2015) - 2014
- [j52]Ido Nevat, Gareth W. Peters, Arnaud Doucet, Jinhong Yuan:
Joint Channel and Doppler Offset Estimation in Dynamic Cooperative Relay Networks. IEEE Trans. Wirel. Commun. 13(12): 6570-6579 (2014) - [c73]