Tootfinder

What would war between EU and Russia actually look like: think WW1 style attrition and the absolute collapse of a way of life that many of us are very comfortable with.
@… is as ever to the point in this one.
https://youtu.be/HwnBnsQBeOA

Physics-informed neural network framework for solving forward and inverse flexoelectric problems
Hyeonbin Moon, Donggeun Park, Jinwook Yeo, Seunghwa Ryu
https://arxiv.org/abs/2506.21810

Physics-informed neural network framework for solving forward and inverse flexoelectric problems
Flexoelectricity, the coupling between strain gradients and electric polarization, poses significant computational challenges due to its governing fourth-order partial differential equations that require C1-continuous solutions. To address these issues, we propose a physics-informed neural network (PINN) framework grounded in an energy-based formulation that treats both forward and inverse problems within a unified architecture. The forward problem is recast as a saddle-point optimization of th…

Seismic resolution enhancement via deep Learning with Knowledge Distillation and Domain Adaptation
Hanpeng Cai, Haonan Zhang, Liyu Zhang, Suo Cheng
https://arxiv.org/abs/2506.22018

Seismic resolution enhancement via deep Learning with Knowledge Distillation and Domain Adaptation
High-resolution processing of seismic signals is crucial for subsurface geological characterization and thin-layer reservoir identification. Traditional high-resolution algorithms can partially recover high-frequency information but often lack robustness, computational efficiency, and consideration of inter-trace structural relationships. Many deep learning methods use end-to-end architectures that do not incorporate prior knowledge or address data domain disparities, leading to limited general…

Wav2Sem: Plug-and-Play Audio Semantic Decoupling for 3D Speech-Driven Facial Animation
Hao Li, Ju Dai, Xin Zhao, Feng Zhou, Junjun Pan, Lei Li
https://arxiv.org/abs/2505.23290

Wav2Sem: Plug-and-Play Audio Semantic Decoupling for 3D Speech-Driven Facial Animation
In 3D speech-driven facial animation generation, existing methods commonly employ pre-trained self-supervised audio models as encoders. However, due to the prevalence of phonetically similar syllables with distinct lip shapes in language, these near-homophone syllables tend to exhibit significant coupling in self-supervised audio feature spaces, leading to the averaging effect in subsequent lip motion generation. To address this issue, this paper proposes a plug-and-play semantic decorrelation …

Dominant Kitaev interaction and field-induced quantum phase transitions in triangular-lattice KCeSe2
Mingtai Xie, Zheng Zhang, Weizhen Zhuo, Wei Xu, Jinfeng Zhu, Jan Embs, Lei Wang, Zikang Li, Huanpeng Bu, Anmin Zhang, Feng Jin, Jianting Ji, Zhongwen Ouyang, Liusuo Wu, Jie Ma, Qingming Zhang
https://arxiv.org/abs/2505.23502

Dominant Kitaev interaction and field-induced quantum phase transitions in triangular-lattice KCeSe2
Realizing Kitaev interactions on triangular lattices offers a compelling platform for exploring quantum-spin-liquid physics beyond the conventional honeycomb lattice framework. Here, we investigate the triangular-lattice antiferromagnet KCeSe2, where multiple probes reveal strong magnetic anisotropy suggesting significant Kitaev physics. Through detailed and combined analysis of magnetization, neutron scattering, and thermodynamic experiments, we identify dominant ferromagnetic Kitaev ($K = -1.…

The high precision time nuts, a.k.a. the “Time Lords” had a pretty good demonstration at #Hamvention. They built an LLM that had ingested 10 years of papers and mailing lists and could answer questions reliably

FICA: Faster Inner Convex Approximation of Chance Constrained Grid Dispatch with Decision-Coupled Uncertainty
Yihong Zhou, Hanbin Yang, Thomas Morstyn
https://arxiv.org/abs/2506.18806

FICA: Faster Inner Convex Approximation of Chance Constrained Grid Dispatch with Decision-Coupled Uncertainty
This paper proposes a Faster Inner Convex Approximation (FICA) method for solving power system dispatch problems with Wasserstein distributionally robust joint chance constraints (WJCC) and incorporating the modelling of the automatic generation control factors. The problem studied belongs to the computationally challenging class of WJCC with left-hand-side uncertainty (LHS-WJCC). By exploiting the special one-dimensional structure (even if only partially present) of the problem, the proposed F…

Roadtripping to #hamvention is an excellent time to spot old #Longwires towers

Antidote est souvent très utile. À d'autres moments, par contre...
Homophone – Ne pas confondre acadien (« habitant de l’Acadie (région du Canada)» ou « langue (l’acadien)») et akkadien (« habitant d’Akkad » ou « langue (l’akkadien)»).

Text-Aware Image Restoration with Diffusion Models
Jaewon Min, Jin Hyeon Kim, Paul Hyunbin Cho, Jaeeun Lee, Jihye Park, Minkyu Park, Sangpil Kim, Hyunhee Park, Seungryong Kim
https://arxiv.org/abs/2506.09993

Text-Aware Image Restoration with Diffusion Models
Image restoration aims to recover degraded images. However, existing diffusion-based restoration methods, despite great success in natural image restoration, often struggle to faithfully reconstruct textual regions in degraded images. Those methods frequently generate plausible but incorrect text-like patterns, a phenomenon we refer to as text-image hallucination. In this paper, we introduce Text-Aware Image Restoration (TAIR), a novel restoration task that requires the simultaneous recovery of…