๋ฐ˜์‘ํ˜•

uncertainty quantification 2

[๋”ฅ๋Ÿฌ๋‹ ๋…ผ๋ฌธ๋ฆฌ๋ทฐ + ์ฝ”๋“œ] What uncertainties do we need in Bayesian deep learning for computer vision? (NeurIPS 2017)

๋…ผ๋ฌธ: https://arxiv.org/pdf/1703.04977.pdf Epistemic uncertainty์™€ aleatoric uncertainty๋ฅผ ๋™์‹œ์— ์ธก์ •ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ฃผ๋Š” ๋ฐฉ๋ฒ•์„ ์†Œ๊ฐœํ•œ ๋…ผ๋ฌธ์ด๋‹ค. ๋…ผ๋ฌธ์„ ๊ฐ„๋‹จํžˆ ์ •๋ฆฌํ•˜๊ณ  PyTorch ์ฝ”๋“œ๋ฅผ ํ•จ๊ป˜ ์†Œ๊ฐœํ•˜๊ณ ์ž ํ•œ๋‹ค. Uncertainty์˜ ์ข…๋ฅ˜ 1. Epistemic uncertainty (=Model uncertainty) ๋ชจ๋ธ๊ตฌ์กฐ๋‚˜ ํ•™์Šต๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋Š” uncertainty์ด๋‹ค. ๋ชจ๋ธ์ด ์ถฉ๋ถ„ํžˆ ํ•™์Šต๋˜์ง€ ์•Š์•˜์„ ์ˆ˜๋„ ์žˆ๊ณ , ์ „์ฒด ๋ฐ์ดํ„ฐ ๋ถ„ํฌ๋ฅผ ๋‹ค ํ•™์Šตํ•˜์ง€ ๋ชปํ–ˆ์„ ์ˆ˜๋„ ์žˆ๊ณ , ๋ชจ๋ธ์˜ ๊ตฌ์กฐ๊ฐ€ ์ง€๋‚˜์น˜๊ฒŒ ๋‹จ์ˆœํ•˜๊ฑฐ๋‚˜ ๋ณต์žกํ•  ์ˆ˜๋„ ์žˆ๋‹ค. Epistemic uncertainty๋Š” ๋ฐ์ดํ„ฐ์…‹ ๋ณด๊ฐ•, ๋ชจ๋ธ ๊ตฌ์กฐ ์ˆ˜์ •, ํ•™์Šต ๋ฐฉ๋ฒ• ๋ณ€๊ฒฝ ๋“ฑ์˜ ๋ฐฉ๋ฒ•์œผ๋กœ ์ค„์ผ ์ˆ˜ ..

[๋”ฅ๋Ÿฌ๋‹ ๋…ผ๋ฌธ๋ฆฌ๋ทฐ + ์ฝ”๋“œ] Uncertainty-Driven Loss for Single Image Super-Resolution (NeurIPS 2021)

NeurIPS 2021์—์„œ ๋ฐœํ‘œ๋œ ๋…ผ๋ฌธ์œผ๋กœ, single image super-resolution (SISR)์„ ์œ„ํ•ด uncertainty๋ฅผ ์ด์šฉํ•œ loss๋ฅผ ์ œ์•ˆํ–ˆ๋‹ค. ๋งจ ์•„๋ž˜์— PyTorch๋กœ ๊ตฌํ˜„๋œ ์ฝ”๋“œ๋ฅผ ์ •๋ฆฌํ•ด ๋†“์•˜๋‹ค. ๋…ผ๋ฌธ ๋งํฌ: https://papers.nips.cc/paper/2021/file/88a199611ac2b85bd3f76e8ee7e55650-Paper.pdf Supplementary: https://papers.nips.cc/paper/2021/file/88a199611ac2b85bd3f76e8ee7e55650-Supplemental.pdf Homepage: https://see.xidian.edu.cn/faculty/wsdong/Projects/UDL-SR.htm https:/..

๋ฐ˜์‘ํ˜•