Miguel Lázaro-Gredilla

According to our database1, Miguel Lázaro-Gredilla authored at least 63 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Diffusion Model Predictive Control.
CoRR, 2024

DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors.
CoRR, 2024

Model Predictive Simulation Using Structured Graphical Models and Transformers.
CoRR, 2024

What type of inference is planning?
CoRR, 2024

Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Fast exploration and learning of latent graphs with aliased observations.
CoRR, 2023

Graph schemas as abstractions for transfer learning, inference, and planning.
CoRR, 2023

3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics.
CoRR, 2023

PushWorld: A benchmark for manipulation planning with tools and movable obstacles.
CoRR, 2023

Schema-learning and rebinding as mechanisms of in-context learning and emergence.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation.
Proceedings of the International Conference on Machine Learning, 2023

3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX.
CoRR, 2022

DURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping.
CoRR, 2021

Perturb-and-max-product: Sampling and learning in discrete energy-based models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
From CAPTCHA to Commonsense: How Brain Can Teach Us About Artificial Intelligence.
Frontiers Comput. Neurosci., 2020

Query Training: Learning and inference for directed and undirected graphical models.
CoRR, 2020

From proprioception to long-horizon planning in novel environments: A hierarchical RL model.
CoRR, 2020

Learning a generative model for robot control using visual feedback.
CoRR, 2020

A Model of Fast Concept Inference with Object-Factorized Cognitive Programs.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019
Learning undirected models via query training.
CoRR, 2019

Learning higher-order sequential structure with cloned HMMs.
CoRR, 2019

2018
Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs.
CoRR, 2018

Cortical Microcircuits from a Generative Vision Model.
CoRR, 2018

Variational Rejection Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Hierarchical compositional feature learning.
CoRR, 2016

2015
Local Expectation Gradients for Black Box Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Biophysical parameter retrieval with warped Gaussian processes.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Neural Networks Learn. Syst., 2014

A Gaussian Process Model for Data Association and a Semidefinite Programming Solution.
IEEE Trans. Neural Networks Learn. Syst., 2014

A Bayesian approach for adaptive multiantenna sensing in cognitive radio networks.
Signal Process., 2014

Retrieval of Biophysical Parameters With Heteroscedastic Gaussian Processes.
IEEE Geosci. Remote. Sens. Lett., 2014

Doubly Stochastic Variational Bayes for non-Conjugate Inference.
Proceedings of the 31th International Conference on Machine Learning, 2014

Laplace approximation with Gaussian Processes for volatility forecasting.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

2013
Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances.
IEEE Signal Process. Mag., 2013

Gaussian Processes for Nonlinear Signal Processing
CoRR, 2013

Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Estimation of vegetation chlorophyll content with Variational Heteroscedastic Gaussian Processes.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

2012
Kernel Recursive Least-Squares Tracker for Time-Varying Regression.
IEEE Trans. Neural Networks Learn. Syst., 2012

Overlapping Mixtures of Gaussian Processes for the data association problem.
Pattern Recognit., 2012

Low-cost model selection for SVMs using local features.
Eng. Appl. Artif. Intell., 2012

Bayesian Warped Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Estimation of the forgetting factor in kernel recursive least squares.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Bayesian multiantenna sensing for cognitive radio.
Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, 2012

2011
Adaptive One-Class Support Vector Machine.
IEEE Trans. Signal Process., 2011

Support Vector Machines With Constraints for Sparsity in the Primal Parameters.
IEEE Trans. Neural Networks, 2011

Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Heteroscedastic Gaussian process regression using expectation propagation.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A Bayesian approach to tracking with kernel recursive least-squares.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A block-based approach to adaptively bias the weights of adaptive filters.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Variational Heteroscedastic Gaussian Process Regression.
Proceedings of the 28th International Conference on Machine Learning, 2011

Tracking performance of adaptively biased adaptive filters.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Adaptively biasing the weights of adaptive filters.
IEEE Trans. Signal Process., 2010

Marginalized neural network mixtures for large-scale regression.
IEEE Trans. Neural Networks, 2010

Sparse Spectrum Gaussian Process Regression.
J. Mach. Learn. Res., 2010

2009
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
A Single Layer Perceptron Approach to Selective Multi-task Learning.
Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

2006
A new cost function to build MLPs by means of regularized boosting.
Proceedings of the Second IASTED International Conference on Computational Intelligence, 2006


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