Showing papers from Brown University Show all papers
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Joint Energy-Based Models show human visual alignment peaks at intermediate generative-discriminative training, not either objective alone.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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History-Aware Prediction Sets (HAPS) construct conformal prediction sets for censored time-to-event outcomes using time-varying covariate histories, reducing interval lengths up to 75% while maintaining coverage among survivors.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A residual-based continuity loss for Wasserstein gradient flows yields a simulation-free stitching method robust to sparse observations and state-of-the-art on trajectory inference benchmarks.
Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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TIDES moves input dependence from step size to the state matrix in selective SSMs, preserving physical time steps and per-token expressivity for irregular series, achieving state-of-the-art time-series results.
Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Deep Probabilistic Supervision constructs sample-specific target distributions via statistical inference on model predictions, improving accuracy, calibration, and label-noise robustness without hard targets.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A fixed-point framework proves looped transformers need recall plus outer normalization for stable, input-dependent extrapolation, validated across chess, sudoku, and prefix-sums tasks.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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RuleSmith uses multi-agent LLM self-play and Bayesian optimization to automatically balance complex games and find highly balanced rule configurations.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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RoPEMover manipulates diffusion transformer position embeddings to move objects with depth-aware 3D geometry, preserving identity, occlusions, and shadows with minimal real data.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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New wavelet-based DPPs offer superior accuracy and a conversion method yields low-rank discrete kernels that preserve variance decay for rough objectives.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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