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Hello，I'm sorry to bother you again. When will the detailed description of the GLUE based optimization method be released? How to get the package for sample R scripts that executes the GLUE-based para…
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in `SAM-6D/Pose_Estimation_Model/run_inference_custom.py: line 205` object proposals with resolution less than 32 pixel is filtered out. It would be useful to get this hyper parameter from the args ra…
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This is truly amazing work!
I'm wondering if you have any suggestions for the best methods to fit the SKEL model to 3d keypoints extracted from a pose estimation model such as mediapipe. Here is w…
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Hi,
I encountered an issue with BMDExpress while recreating an experiment from a published paper. The analysis results I obtained using BMDExpress differed from those reported in the paper. After c…
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Your work is truly impressive. Thank you for your contribution to code review task!
I meet some problem with your **code refine task code.**
As you say in your paper, you use a teach model for …
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Secure gas cost estimation is hard and not well explored. The closest well-known thing is benchmarking systems to compare performance. That itself is already non-trivial. But people have studied it, c…
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# Your Hack Title
Estimate the parameters of strong gravitational lenses with neural nets in a likelihood-free setting
Contacts: Yashar Hezaveh, Laurence Perreault Levasseur,
Participants: Me
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http://web4.cs.ucl.ac.uk/staff/d.barber/publications/gpodeICML2014.pdf
https://papers.nips.cc/paper/3497-accelerating-bayesian-inference-over-nonlinear-differential-equations-with-gaussian-processes
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Distributed has a lot of overhead. I think we should return to providing also multi-threaded assembly of linear systems
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Thanks for presenting – this work is really cool!
I was curious about one of your model's parameters and how it was estimated. On page 9, you discuss parameterizing the symmetric trade cost functio…