15 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Pathfinder models and implementations
2 papers

Most implemented papers

Pathfinder: Parallel quasi-Newton variational inference

luzhangstat/pathfinder 9 Aug 2021

Pathfinder returns draws from the approximation with the lowest estimated Kullback-Leibler (KL) divergence to the true posterior.

RadioGalaxyNET: Dataset and Novel Computer Vision Algorithms for the Detection of Extended Radio Galaxies and Infrared Hosts

nikhel1/gal-detr 1 Dec 2023

Creating radio galaxy catalogues from next-generation deep surveys requires automated identification of associated components of extended sources and their corresponding infrared hosts.

Simplified State Space Layers for Sequence Modeling

lindermanlab/S5 9 Aug 2022

Models using structured state space sequence (S4) layers have achieved state-of-the-art performance on long-range sequence modeling tasks.

AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks

kgourgou/adaptive-importance-sampling-BN 1 Jun 2011

Stochastic sampling algorithms, while an attractive alternative to exact algorithms in very large Bayesian network models, have been observed to perform poorly in evidential reasoning with extremely unlikely evidence.

Path-Restore: Learning Network Path Selection for Image Restoration

yuke93/Path-Restore 23 Apr 2019

To leverage this, we propose Path-Restore, a multi-path CNN with a pathfinder that can dynamically select an appropriate route for each image region.

CAESAR source finder: recent developments and testing

SKA-INAF/caesar 13 Sep 2019

Given the increased scale of the data, source extraction and characterization, even in this Early Science phase, have to be carried out in a mostly automated way.

Point Proposal Network: Accelerating Point Source Detection Through Deep Learning

tilleyd/point-proposal-net 5 Aug 2020

Point source detection techniques are used to identify and localise point sources in radio astronomical surveys.

Pathfinder Discovery Networks for Neural Message Passing

benedekrozemberczki/PDN 24 Oct 2020

Additional results from a challenging suite of node classification experiments show how PDNs can learn a wider class of functions than existing baselines.

Chaotic World: A Large and Challenging Benchmark for Human Behavior Understanding in Chaotic Events

sutdcv/chaotic-world ICCV 2023

Understanding and analyzing human behaviors (actions and interactions of people), voices, and sounds in chaotic events is crucial in many applications, e. g., crowd management, emergency response services.

Searching for long faint astronomical high energy transients: a data driven approach

rcrupi/deepgrb 28 Mar 2023

The main objective of HERMES Pathfinder is to prove that accurate position of high-energy cosmic transients can be obtained using miniaturized hardware.