Event owner lens
Use this record to benchmark whether a comparable event makes the work after the room visible. The score is 36/100, so the next move is to benchmark the weakest pillars before repeating the format.
broadcast-heavy conference agenda analysis
ICLR - Diffusion On Syntax Trees For Program Synthesis - Workshops - Machine Learning Multiscale Processes
This broadcast-heavy conference in Technology / AI / Startup shows 29 visible agenda rows from iclr.cc and scores 36/100: a thin but inspectable design signal. The clearest public signals sit in Future-of-Work Fit and Participation Architecture; the main limits are Follow Through and Network Design. Visible mechanisms include Participant work, Feedback, Network design, and Learning transfer. The public record does not show follow-up or tracking, so the score should be read as design intent rather than durable... A practical reading: For a reader, this is a comparison record more than a model to copy: it reads as a broadcast-heavy conference, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence. This page is an original public-evidence analysis, not a copy of the source agenda or an endorsement of the event. The score places the visible agenda in the thin outcome architecture band. The strongest visible pillars are Future-of-Work Fit, Participation Architecture, and Problem Specificity; the thinnest visible pillars are Follow Through, Network Design, and Learning Transfer. Visible mechanisms include Participant work, Feedback, Network design, and Learning transfer. The extracted agenda preview includes 52 visible rows. The most common formats are Unknown, Presentation, and Poster Session; the most common inferred purposes are Unknown, Knowledge Transfer, and Showcase.
Eight-pillar fingerprint
Hover any pillar to see what it measures and, where it scored low, what the agenda is missing.
Participation Architecture?50
Participation Architecture - 50/100. Participant work, contribution, interaction, and alternatives to passive broadcast.
Follow Through?5
Follow Through - 5/100. Owners, dates, commitments, progress checks, and accountability after the room.Missing: Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
Problem Specificity?47
Problem Specificity - 47/100. A clear costly problem, objective, decision, or performance target.
Personalization?33
Personalization - 33/100. Role, path, goal, preparation, or connection tailoring for participants.
Network Design?16
Network Design - 16/100. Structured weak ties, bridge-building, mixers, and relationship persistence.Missing: Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
Learning Transfer?32
Learning Transfer - 32/100. Applied practice, feedback, workplace use, refreshers, and 30-90 day transfer.Missing: Build transfer into the agenda through practice, feedback, job aids, reflection, and 30-90 day use cases.
Evidence Maturity?45
Evidence Maturity - 45/100. Baseline, comparison, follow-up, isolation, and attribution confidence.
Future-of-Work Fit?59
Future-of-Work Fit - 59/100. Value against time, hybrid reality, accessibility, AI, and meeting load.
Fix the gaps
Field-tested exercises matched to this agenda's weakest pillars, from the exercise library.
Follow Through (5/100)
Exercises that strengthen it: Mental Toughness Workshop • WorkshopBank · 15% Solutions • WorkshopBank · Network Patches
Network Design (16/100)
Exercises that strengthen it: Fun Trust-Building Group Game for Team Connection - Izzat... · Exciting Group Trust Activity for Building Confidence... · PFP: September 2005
Learning Transfer (32/100)
Exercises that strengthen it: Team Challenge Activity for Group Problem-Solving: Don't... · Thrilling, Quick Elimination Game to Boost Energy - Match... · Creative Brain Teaser & Fun Geometric Team Puzzle - T-Puzzle
Agenda Preview
The actual agenda we captured. Every block is classified by format and purpose. Open any block to see how we read it; the colored edge shows whether it is participant work, broadcast, logistics, or a showcase.
Room vs wrapper
17 percent of the 52 classified blocks put participants to work; the rest broadcast, show, or handle logistics. That mix is what drives the participation score.
Participant workBroadcastShowcaseLogistics
all eventBlog Track PostersPoster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
all eventWorkshopsWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
all eventWorkshopWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
5:30 PMPoster SetupPoster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
5:45 PMOpening remarks Nikita Kazeev VideoOpeningOrientation+
Format · BroadcastOpeningFormat not classified from the source; treated as a broadcast block by default.
Evidence basisNo participant output visible from this rowRead from source, no work signal
6:00 PMFunctional Intelligent Materials Kostya Novoselov Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
6:30 PMMath + AI = AGI Sergei Gukov Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
7:00 PMCoffee BreakBreakPacing+
Format · LogisticsBreakA pacing or recovery block between sessions.
Evidence basisOutcome inferred from formatInferred from format
7:30 PMOn the successful Incorporation of Scale into Graph Neural Networks Christian Koke ⋅ Yuesong Shen ⋅ Abhishek Saroha ⋅ Marvin Eisenberger ⋅ Bastian Rieck ⋅ Michael Bronstein ⋅ Daniel Cremers Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
7:45 PMConstructing macroscopic dynamics using deep learning Qianxiao Li Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
8:15 PMVirtual Cells and Digital Twins: Multi-Scale and Multi-Modal AI for Biomedicine Charlotte Bunne Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
8:45 PMQ&A and Panel Discussion Eleonore Vissol-Gaudin ⋅ Kostya Novoselov ⋅ Sergei Gukov ⋅ Christian Koke ⋅ Qianxiao Li ⋅ Charlotte Bunne Video LinkPanelDiscussion+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisNo participant output visible from this rowRead from source, no work signal
9:15 PM10:15 PM DoMiNO: Down-scaling Molecular Dynamics with Neural Graph Ordinary Differential Equations Fang Sun ⋅ Zijie Huang ⋅ Yadi Cao ⋅ Xiao Luo ⋅ Wei Wang ⋅ Yizhou Sun Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
10:15 PMDoMiNO: Down-scaling Molecular Dynamics with Neural Graph Ordinary Differential Equations Fang Sun ⋅ Zijie Huang ⋅ Yadi Cao ⋅ Xiao Luo ⋅ Wei Wang ⋅ Yizhou Sun Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
10:30 PMSpotlight Talks Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
11:00 PMPoster Session LinkPoster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
12:30 AMLOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators Marimuthu Kalimuthu ⋅ Daniel Musekamp ⋅ David Holzmüller ⋅ Mathias Niepert Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
12:45 AM5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence Gianluca Galletti ⋅ Fabian Paischer ⋅ Paul Setinek ⋅ William Hornsby ⋅ Lorenzo Zanisi ⋅ Naomi Carey ⋅ Stanislas Pamela ⋅ Johannes Brandstetter Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:00 AMOn a Method for the Hierarchical Modeling of Complex Hamiltonian Systems Daniel Polani Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:30 AMQ&A and Panel Discussion Paul Setinek ⋅ Nikita Kazeev ⋅ Charlotte Bunne ⋅ Daniel Polani ⋅ Yizhou Sun ⋅ Daniel Musekamp Video LinkPanelDiscussion+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:50 AMThe (Near) Future of Multiscale ML Andrey Ustyuzhanin VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
2:40 AMCollaboration Pitches LinkWorkshopMarket exchange+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
2:50 AMClosung Remarks Nikita Kazeev ⋅ Eleonore Vissol-Gaudin ⋅ Mengyi Chen ⋅ Bingjia Yang ⋅ Andrey Ustyuzhanin VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
all eventMain ConferenceUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventBlog Track PostersPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
all eventWorkshopsWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventCommunityUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventWorkshopWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventSome of the most exciting and impactful open scientific problems have computational complexity as the limiting factor to an in silico solution, e. g. high - temperature superconductivity and fusion power. Atoms behave according to the well - established laws of quantum mechanics, but as system size grows computations quickly become intractable. This workshop will gather for cross - pollination a diverse group of researchers belonging to difference scientific domains and machine learning approaches. The immediate outcome will be an exchange of ideas, datasets, and crystallized problem statements, all towards the ultimate goal of developing universal AI methods that would be able find efficient and accurate approximations of complex systems from low-level theory. If we solve scale transition, we solve science.WorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventTimezone: America/LosAngelesUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
5:30 PMPoster SetupPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
5:45 PMOpening remarks Nikita Kazeev VideoOpening RemarksOrientation+
Format · BroadcastOpening RemarksFraming or welcome from the stage. Orients the room, not participatory.
Evidence basisMediumRead from source
6:00 PMFunctional Intelligent Materials Kostya Novoselov Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
6:30 PMMath + AI = AGI Sergei Gukov Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
7:00 PMCoffee BreakBreakWellbeing+
Format · LogisticsBreakA pacing or recovery block between sessions.
Evidence basisMediumRead from source
7:30 PMOn the successful Incorporation of Scale into Graph Neural Networks Christian Koke ⋅ Yuesong Shen ⋅ Abhishek Saroha ⋅ Marvin Eisenberger ⋅ Bastian Rieck ⋅ Michael Bronstein ⋅ Daniel Cremers Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
7:45 PMConstructing macroscopic dynamics using deep learning Qianxiao Li Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
8:15 PMVirtual Cells and Digital Twins: Multi-Scale and Multi-Modal AI for Biomedicine Charlotte Bunne Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
8:45 PMQ&A and Panel Discussion Eleonore Vissol-Gaudin ⋅ Kostya Novoselov ⋅ Sergei Gukov ⋅ Christian Koke ⋅ Qianxiao Li ⋅ Charlotte Bunne Video LinkPanelDeliberation+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisMediumRead from source
9:15 PM10:15 PM DoMiNO: Down-scaling Molecular Dynamics with Neural Graph Ordinary Differential Equations Fang Sun ⋅ Zijie Huang ⋅ Yadi Cao ⋅ Xiao Luo ⋅ Wei Wang ⋅ Yizhou Sun Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
10:15 PMDoMiNO: Down-scaling Molecular Dynamics with Neural Graph Ordinary Differential Equations Fang Sun ⋅ Zijie Huang ⋅ Yadi Cao ⋅ Xiao Luo ⋅ Wei Wang ⋅ Yizhou Sun Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
10:30 PMSpotlight Talks Video LinkPresentationKnowledge Transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisMediumRead from source
11:00 PMPoster Session LinkPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
12:30 AMLOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators Marimuthu Kalimuthu ⋅ Daniel Musekamp ⋅ David Holzmüller ⋅ Mathias Niepert Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
12:45 AM5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence Gianluca Galletti ⋅ Fabian Paischer ⋅ Paul Setinek ⋅ William Hornsby ⋅ Lorenzo Zanisi ⋅ Naomi Carey ⋅ Stanislas Pamela ⋅ Johannes Brandstetter Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
1:00 AMOn a Method for the Hierarchical Modeling of Complex Hamiltonian Systems Daniel Polani Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
1:30 AMQ&A and Panel Discussion Paul Setinek ⋅ Nikita Kazeev ⋅ Charlotte Bunne ⋅ Daniel Polani ⋅ Yizhou Sun ⋅ Daniel Musekamp Video LinkPanelDeliberation+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisMediumRead from source
1:50 AMThe (Near) Future of Multiscale ML Andrey Ustyuzhanin VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
2:40 AMCollaboration Pitches LinkPitchCommercial Exchange+
Format · Participant workPitchParticipants present or are directly evaluated, an active rather than a passive format.
Evidence basisMediumRead from source
2:50 AMClosung Remarks Nikita Kazeev ⋅ Eleonore Vissol-Gaudin ⋅ Mengyi Chen ⋅ Bingjia Yang ⋅ Andrey Ustyuzhanin VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
all eventFlow Domain Parameterization and Training of Generalized Physics-Informed Neural Networks for Solving Navier-Stokes Equations Ivan Stebakov ⋅ Alexei Kornaev ⋅ Elena Kornaeva LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
all eventHard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings Christopher Straub ⋅ Philipp Brendel ⋅ Vlad Medvedev ⋅ Andreas Rosskopf LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
The Full Reading
Why It Ranks This Way +
Calibrated from GES design 35/100 and verified 36/100 with no fourth-loop cap.
Reader Takeaway. For a reader, this is a comparison record more than a model to copy: it reads as a broadcast-heavy conference, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence.
Strongest signals: Future-of-Work Fit, Participation Architecture, and Problem Specificity. Weakest signals: Follow Through, Network Design, and Learning Transfer.
How This Agenda Could Improve +
- Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
- Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
- Build transfer into the agenda through practice, feedback, job aids, reflection, and 30-90 day use cases.
Fastest next move: Add named owners, dated next steps, and a visible continuation path before treating the event as outcome-ready.
Role-Specific Reading +
Sponsor lens
Look beyond exposure. Strong sponsor value would show qualified interaction, problem work, buyer learning, customer evidence, or follow-up. The practical sponsor move is to look for structured introductions, buyer-seller fit, and relationship persistence.
Designer lens
The agenda is useful as a pattern sample from iclr.cc. Redesign attention should go first to the lowest-scoring pillars; in practice, turn the thinnest agenda blocks into participant work.
Executive lens
Treat the visible agenda as an operating plan. The executive move is to require owners, dates, and evidence before treating the event as strategic. If owners, proof, and follow-through are not visible, the public record does not yet prove strategic movement.
Aggregator lens
Treat the source URL as evidence, not decoration. The data-product move is to label the source boundary clearly before ranking the record before ranking or syndicating the record.
What GES Means Here +
The Gathering Effectiveness Score is a strict 0-100 public-evidence reading of the agenda across eight pillars. It rewards visible participant work, follow-through, transfer, network design, and proof mechanisms more than polish, speaker fame, attendance, or satisfaction.
Visible mechanisms: Participant work, Feedback, Network design, Learning transfer.
Evidence boundary: Scores reflect visible agenda/source evidence and should not be read as proof of causal event impact.
Limitations, Score Caps, and Review Flags +
Limitations
- No visible follow-up, progress monitoring, or longitudinal tracking.
- Passive stage formats dominate the visible agenda.
- No baseline measurement is visible.
Score caps
- No fourth-loop score cap applied.
Review flags
- No source-backed follow-up, validation, baseline, tracking, or impact evidence.
- No tracking, validation, feedback, or impact measurement found in the visible source text.
Is this proof the event worked? +
No. This is a strict public-evidence reading of the agenda. Proof would require baseline, comparison, follow-up, attribution, and impact evidence beyond the listing.
What should a reader inspect first? +
Start with the source URL, then compare the eight pillar scores against the agenda rows. The biggest opportunities usually sit in follow-through, evidence maturity, and participant work.
Why publish weak records? +
Weak records are part of the map. They show where public agendas still describe sessions and speakers more often than outcomes, commitments, transfer, or proof.
How should I use the rows? +
Read the agenda rows as the visible design trace: formats, purposes, and evidence labels show what the public source made inspectable, not everything that happened in the room. This is a source-grounded interpretation of the public agenda record, not a copy of the source, and not an endorsement of the event.
Embed the verified badge +
This record is in the hand-verified gold set. Copy the snippet below to embed the verified badge on your own site.
<a href="https://unitedwetransform.com/events/evt_2025_iclr_diffusion_on_syntax_trees_for_program_synthesis_workshops_machine_lear"><img src="https://unitedwetransform.com/badge/ges-verified.svg" alt="GES verified by United We Transform" height="40"></a>Where To Go Next
Compare this agenda against other Technology / AI / Startup events scored on the same eight pillars.