http://arno.solin.fi
#BitVI directly learns an approximation in the space of bitstring representations, thus, capturing complex distributions under varying numerical precision regimes.
I’m giving an invited talk in the ”Calibrating prediction uncertainty : statistics and machine learning perspectives” workshop on Thursday.
I’m giving an invited talk in the ”Calibrating prediction uncertainty : statistics and machine learning perspectives” workshop on Thursday.
1/3
1/3
🗓️ Hall 3 + Hall 2B #416, Fri 25 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2408.02346
🗓️ Hall 3 + Hall 2B #416, Fri 25 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2408.02346
🗓️ Hall 3 + Hall 2B #194, Fri 25 Apr 3 p.m. +08 — 5:30 p.m. +08
📄 Preprint: arxiv.org/abs/2405.17656
🗓️ Hall 3 + Hall 2B #194, Fri 25 Apr 3 p.m. +08 — 5:30 p.m. +08
📄 Preprint: arxiv.org/abs/2405.17656
🗓️ Hall 3 + Hall 2B #413, Fri 25 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2411.18425
🗓️ Hall 3 + Hall 2B #413, Fri 25 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2411.18425
🗓️ Hall 3 + Hall 2B #415, Thu 24 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2503.00653
🗓️ Hall 3 + Hall 2B #415, Thu 24 Apr 10 a.m. +08 — 12:30 p.m. +08
📄 Preprint: arxiv.org/abs/2503.00653
🗓️ Hall 3 + Hall 2B #140, Thu 24 Apr 3 p.m. +08 — 5:30 p.m. +08
📄 Preprint: arxiv.org/abs/2410.11149
🗓️ Hall 3 + Hall 2B #140, Thu 24 Apr 3 p.m. +08 — 5:30 p.m. +08
📄 Preprint: arxiv.org/abs/2410.11149
Then join the oral presentation by @ruili-pml.bsky.social of our paper!
🔗 lnkd.in/dBMmN7Vs
Done together with @marcusklasson.bsky.social and @arnosolin.bsky.social.
Then join the oral presentation by @ruili-pml.bsky.social of our paper!
🔗 lnkd.in/dBMmN7Vs
Done together with @marcusklasson.bsky.social and @arnosolin.bsky.social.
I have been giving a crash course as part of the #Nordita Winter School on "Physics of Machine Learning & Machine Learning for Physics“ in Stockholm.
Great interaction with young physicists and new avenues for applying ML. ✨
I have been giving a crash course as part of the #Nordita Winter School on "Physics of Machine Learning & Machine Learning for Physics“ in Stockholm.
Great interaction with young physicists and new avenues for applying ML. ✨
📝 Paper pre-print: arxiv.org/abs/2409.13876
📝 Paper pre-print: arxiv.org/abs/2409.13876
🔗 to extended versions:
1. 🙋 "How can we make predictions in BDL efficiently?" 👉 arxiv.org/abs/2411.18425
2. 🙋 "How can we do prob. active learning in VLMs" 👉 arxiv.org/abs/2412.06014
🔗 to extended versions:
1. 🙋 "How can we make predictions in BDL efficiently?" 👉 arxiv.org/abs/2411.18425
2. 🙋 "How can we do prob. active learning in VLMs" 👉 arxiv.org/abs/2412.06014
Here’s my current team at Aalto University: users.aalto.fi/~asolin/group/
Here’s my current team at Aalto University: users.aalto.fi/~asolin/group/
Yihao Wang, Marcus Klasson, Matias Turkulainen, Shuzhe Wang, Juho Kannala, @arnosolin.bsky.social
tl;dr: decompose alpha compositing and explicitly separate occluders and the underlying static 3D scene
arxiv.org/abs/2411.19756
Yihao Wang, Marcus Klasson, Matias Turkulainen, Shuzhe Wang, Juho Kannala, @arnosolin.bsky.social
tl;dr: decompose alpha compositing and explicitly separate occluders and the underlying static 3D scene
arxiv.org/abs/2411.19756