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Incorporating Neural Network Structure in the Bayesian Learning Rule

Eiki Shimizu, Mohammad Emtiyaz Khan, Thomas Möllenhoff

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Score-based Variational Inference via Quantum Maximally Mixed States

Yuchen CONG, Zerui Tao, Chao Li, Zhe Sun and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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The Bayesian Learning Rule Beyond KL Geometry

SOPHIA SKLAVIADIS, Wu Lin, Mario Figueiredo, André Martins and 2 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels

mohit sharma, Okan Koc, Amit Jayant Deshpande, Takashi Ishida and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NoTA: Normalized Tensor Adaptation for Parameter-Efficient Continual Learning

Yunsong Deng, Yuning Qiu, Qibin Zhao, Guoxu Zhou

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
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57%Worth a look
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Beyond Exemplar Selection: Value-Aware Memory Allocation in Replay-Based Continual Learning

Yuhang Li, Guoxu Zhou, Zhenhao Huang, Yuning Qiu and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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71%Highly rated
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PPO in the Fisher-Rao geometry

FR-PPO leverages Fisher-Rao geometry to provide monotonic policy improvement guarantees and sub-linear convergence without dependence on state or action space dimensions.

Razvan-Andrei Lascu, David Siska, Lukasz Szpruch

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 7 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 1/5
72%Highly rated
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Mirror Descent-Ascent for mean-field min-max problems

Mirror descent-ascent achieves O(N^{-1/2}) and O(N^{-2/3}) convergence to mean-field Nash equilibria via infinite-dimensional dual Bregman analysis.

Razvan-Andrei Lascu, Mateusz Majka, Lukasz Szpruch

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 2/5
medium 4/10
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92%Must read
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Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability

Cross-modal redundancy causes unimodal metrics to contradict (τ=-0.06), so Synergistic Faithfulness (F_syn) isolates joint modality dividends with ρ=0.92 and 24× speedup, revealing VLM explainers over-index visual salience versus adapted attention methods.

Joël Roman Ky, Salah GHAMIZI, Maxime Cordy

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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AI panel: 19 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 4/5
71%Highly rated
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Guided Data Generation for Understanding Model Behavior

A guided data generation framework generates input distributions to inspect trained model behaviors via specification functions.

Eren Mehmet KIRAL, Nursen Aydin, Ilker Birbil

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 6 of 20 reviewers recommend it
lenient 4/5
medium 1/10
strict 1/5
71%Highly rated
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Flow Matching from Viewpoint of Proximal Operators

Optimal transport conditional flow matching equals exact proximal operators via extended Brenier potentials without density assumptions, yields explicit vector fields, converges with batch size, and contracts exponentially normal to manifold-supported targets.

Kenji Fukumizu, Wei Huang, Han Bao, Shuntuo Xu and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 7 of 20 reviewers recommend it
lenient 2/5
medium 3/10
strict 2/5
80%Must read
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Structured Unitary Tensor Network Representations for Circuit-Efficient Quantum Data Encoding

TNQE uses structured unitary tensor networks to learn shallow, resource-efficient quantum data encoding circuits that achieve 0.04x the depth of amplitude encoding and scale to high-resolution images on real hardware.

Guang Lin, Toshihisa Tanaka, Qibin Zhao

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5