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06/02/2023
Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes
Robotic Information Gathering (RIG) is a foundational research topic tha...
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02/05/2023
Direct Uncertainty Quantification
Traditional neural networks are simple to train but they produce overcon...
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02/03/2023
DiSProD: Differentiable Symbolic Propagation of Distributions for Planning
The paper introduces DiSProD, an online planner developed for environmen...
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11/15/2022
On the Performance of Direct Loss Minimization for Bayesian Neural Networks
Direct Loss Minimization (DLM) has been proposed as a pseudo-Bayesian me...
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06/16/2022
Explainable Models via Compression of Tree Ensembles
Ensemble models (bagging and gradient-boosting) of relational decision t...
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05/13/2022
AK: Attentive Kernel for Information Gathering
Robotic Information Gathering (RIG) relies on the uncertainty of a proba...
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03/23/2022
Approximate Inference for Stochastic Planning in Factored Spaces
Stochastic planning can be reduced to probabilistic inference in large d...
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04/07/2020
Direct loss minimization for sparse Gaussian processes
The Gaussian process (GP) is an attractive Bayesian model for machine le...
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01/04/2017
Stochastic Planning and Lifted Inference
Lifted probabilistic inference (Poole, 2003) and symbolic dynamic progra...
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07/05/2014
The Complexity of Reasoning with FODD and GFODD
Recent work introduced Generalized First Order Decision Diagrams (GFODD)...
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01/16/2014
Probabilistic Relational Planning with First Order Decision Diagrams
Dynamic programming algorithms have been successfully applied to proposi...
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01/22/2013
Online Learning with Pairwise Loss Functions
Efficient online learning with pairwise loss functions is a crucial comp...
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11/28/2012
Nonparametric Bayesian Mixed-effect Model: a Sparse Gaussian Process Approach
Multi-task learning models using Gaussian processes (GP) have been devel...
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03/05/2012
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to impr...
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10/31/2011