Joey Bose
@bose_joey
Followers
3K
Following
10K
Media
85
Statuses
1K
Incoming Assistant Professor @imperialcollege and @Mila_Quebec Affiliate member. Into Geometry ∩ Generative Models and AI4Science. Phd @Mila_Quebec / McGill.
London
Joined January 2018
🎉Personal update: I'm thrilled to announce that I'm joining Imperial College London @imperialcollege as an Assistant Professor of Computing @ICComputing starting January 2026. My future lab and I will continue to work on building better Generative Models 🤖, the hardest.
97
34
603
What a pleasant end to #ICML2025 to win the best paper at @genbio_workshop with the dream team for our paper. FORT: Forward only regression training of Normalizing flows 🌊.
Wrapping up #ICML2025 on a high note — thrilled (and pleasantly surprised!) to win the Best Paper Award at @genbio_workshop 🎉. Big shoutout to the team that made this happen!. Paper: Forward-Only Regression Training of Normalizing Flows ( . @Mila_Quebec
5
4
84
RT @AndreiRekesh: 📢We are excited to share SynCoGen—the first generative model that co-generates 🔷building-block graphs,🔷reaction edges and….
0
24
0
RT @martoskreto: we’re not kfc but come watch us cook with our feynman-kac correctors, 4:30 pm today (july 16) at @icmlconf poster session….
0
15
0
RT @AlexanderTong7: Come check out SBG happening now! W-115 11-1:30 with.@charliebtan .@bose_joey .Chen Lin.@leonklein26 .@mmbronstein http….
0
16
0
RT @karsten_kreis: 📢📢 "La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching". Fully atomistic. Partially latent. St….
0
33
0
GenBio Workshop SPOTLIGHT Presentation . 📜 Title: Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities. 🕐 When: Fri 18 Jul. 🗺️ Where: East Exhibition Hall A. 🔗 arXiv: w/ @tara_aksa @yololulu_ @ValentinDeBort1.
0
2
10
GenBio Workshop ORAL Presentation. 📜 Title: FORT: Forward-Only Regression Training of Normalizing Flows. 🕐 When: Fri 18 Jul . 🗺️ Where: East Exhibition Hall A. 🔗 arXiv: w/ @danyalrehman17 @osclsd @jiarlu @tangjianpku @mmbronstein @Yoshua_Bengio.
1
5
9
Main Conference:. 📜 Title: Scalable Equilibrium Sampling with Sequential Boltzmann Generators. 🕐 When: Wed 16 Jul 11 a.m. PDT — 1:30 p.m. PDT. 🗺️ Where: West Exhibition Hall B2-B3 W-115. 🔗 arXiv: w/ @charliebtan @WillLin1028 @leonklein26 @mmbronstein.
arxiv.org
Scalable sampling of molecular states in thermodynamic equilibrium is a long-standing challenge in statistical physics. Boltzmann generators tackle this problem by pairing normalizing flows with...
1
2
7
👋 I'm at #ICML2025 this week, presenting several papers throughout the week with my awesome collaborators! . Please do reach out if you'd like to grab a coffee ☕️ or catch up again!. Papers in 🧵below 👇:.
1
7
62
RT @pranamanam: The Programmable Biology Group is en route to Vancouver for #ICML2025!! 🇨🇦🗻 Please come by my student's posters -- they wou….
0
11
0
RT @jacobbamberger: 🚨 ICML 2025 Paper 🚨. "On Measuring Long-Range Interactions in Graph Neural Networks". We formalize the long-range probl….
0
17
0
RT @AlexanderTong7: Thrilled to be co-organizing FPI at #NeurIPS2025! I'm particularly excited about our new 'Call for Open Problems'track.….
0
2
0
🚨 Our workshop on Frontiers of Probabilistic Inference: Learning meets Sampling got accepted to #NeurIPS2025!!. After the incredible success of the first edition. The second edition is aimed to be bolder, bigger, and more ambitious in outlining key challenges in the natural.
1/ Where do Probabilistic Models, Sampling, Deep Learning, and Natural Sciences meet? 🤔 The workshop we’re organizing at #NeurIPS2025!. 📢 FPI@NeurIPS 2025: Frontiers in Probabilistic Inference – Learning meets Sampling. Learn more and submit →
2
3
54
RT @riashatislam: If you are into generative models and interested in applications of it in AI4Science - @bose_joey is an amazing person to….
0
1
0
I also want to take this time to thank all the people who have supported and continue to support my research journey. Especially @mmbronstein at @UniofOxford, the awesome ML community @Mila_Quebec (special shoutout to my PhD advisors @gauthier_gidel and Prakash Panangaden), and.
0
0
26
RT @stefanhoroi: 🔎Do better expert models always lead to better model merging & MoErging? And how does expert training (duration) affect mo….
0
5
0
RT @benno_krojer: Started a new podcast with @tvergarabrowne !. Behind the Research of AI: .We look behind the scenes, beyond the polished….
0
13
0
RT @AlexanderTong7: A bit of backstory on PITA: the project started with a key goal—to fix the inherent bias in prior diffusion samplers (l….
0
4
0
RT @AlexanderTong7: iDEM introduced a very effective but biased training scheme for diffusion-based samplers. This….
arxiv.org
Efficiently generating statistically independent samples from an unnormalized probability distribution, such as equilibrium samples of many-body systems, is a foundational problem in science. In...
0
2
0