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08/30/2023
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation
For robots to be useful outside labs and specialized factories we need a...
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02/14/2023
Graph schemas as abstractions for transfer learning, inference, and planning
We propose schemas as a model for abstractions that can be used for rapi...
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02/07/2023
3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics
A central challenge in 3D scene perception via inverse graphics is robus...
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01/31/2023
Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation
Noisy-OR Bayesian Networks (BNs) are a family of probabilistic graphical...
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02/08/2022
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX
PGMax is an open-source Python package for easy specification of discret...
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01/20/2022
Metropolis Augmented Hamiltonian Monte Carlo
Hamiltonian Monte Carlo (HMC) is a powerful Markov Chain Monte Carlo (MC...
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12/06/2021
Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping
Discrete undirected graphical models, also known as Markov Random Fields...
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10/19/2021
Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center
Load balancing is vital for the efficient and long-term operation of clo...
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05/10/2021
Deep Reinforcement Learning-based Methods for Resource Scheduling in Cloud Computing: A Review and Future Directions
As the quantity and complexity of information processed by software syst...
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06/11/2020
Query Training: Learning and inference for directed and undirected graphical models
Probabilistic graphical models (PGMs) provide a compact representation o...
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09/11/2019