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We construct a theoretical model for the dynamics of a microscale colloidal particle, modeled as an interval, moving horizontally on a DNA-coated surface, modelled as a line coated with springs that can stick to the interval. Averaging over…

Soft Condensed Matter · Physics 2018-09-28 James P. Lee-Thorp , Miranda Holmes-Cerfon

Model diffing methods aim to identify how fine-tuning changes a model's internal representations. Crosscoders approach this by learning shared dictionaries of interpretable latent directions between base and fine-tuned models. However,…

Machine Learning · Computer Science 2026-03-06 Aly Kassem , Thomas Jiralerspong , Negar Rostamzadeh , Golnoosh Farnadi

Foundation segmentation models such as Segment Anything Model (SAM) are now routinely used in iterative pipelines, where each predicted mask is fed back as the next prompt. This practice turns segmentation into a closed-loop dynamical…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 H. M. Shadman Tabib , Md. Shamsuzzoha Bayzid , M Sohel Rahman

Decoder-only language models are stateless: hidden representations are discarded after every forward pass and nothing persists across sessions. Jeong (2026a) showed that trained memory adapters give a frozen encoder-decoder backbone…

Machine Learning · Computer Science 2026-03-25 Hong Jeong

Data-driven and controllable human motion synthesis and prediction are active research areas with various applications in interactive media and social robotics. Challenges remain in these fields for generating diverse motions given past…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Wenjie Yin , Ruibo Tu , Hang Yin , Danica Kragic , Hedvig Kjellström , Mårten Björkman

We investigate the translational motion of rotating colloidal systems at moderate Reynolds numbers (Re), focusing on particle dimers in snowman-like configurations under three scenarios: (i) two co-rotating spheres driven by an external…

Soft Condensed Matter · Physics 2025-06-04 Zaiyi Shen , Dongfang Fu , Juho Lintuvuori

In recent years, molecular graph representation learning (GRL) has drawn much more attention in molecular property prediction (MPP) problems. The existing graph methods have demonstrated that 3D geometric information is significant for…

Machine Learning · Computer Science 2022-12-01 Hao Zhang , Nan Zhang , Ruixin Zhang , Lei Shen , Yingyi Zhang , Meng Liu

Simulations of biological macromolecules play an important role in understanding the physical basis of a number of complex processes such as protein folding. Even with increasing computational power and evolution of specialized…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-18 Hyungro Lee , Heng Ma , Matteo Turilli , Debsindhu Bhowmik , Shantenu Jha , Arvind Ramanathan

Generative modeling of physical systems, such as molecules, requires learning distributions that are invariant under global symmetries, such as rotations in three-dimensional space. Equivariant diffusion and flow matching models can…

Machine Learning · Computer Science 2026-05-08 Samir Darouich , Vinh Tong , Lluís Pastor-Pérez , Tanja Bien , Loay Mualem , Mathias Niepert

Molecular 3D conformations play a key role in determining how molecules interact with other molecules or protein surfaces. Recent deep learning advancements have improved conformation prediction, but slow training speeds and difficulties in…

Machine Learning · Computer Science 2024-12-17 Qingwen Tian , Yuxin Xu , Yixuan Yang , Zhen Wang , Ziqi Liu , Pengju Yan , Xiaolin Li

Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such landscapes are difficult to learn from data and, once learned, hard to sample from.…

Machine Learning · Computer Science 2026-05-19 Christoph Griesbacher , Lea Bogensperger , Andreas Habring , Thomas Pock

Traditional discriminative computer vision relies predominantly on static projections, mapping input features to outputs in a single computational step. Although efficient, this paradigm lacks the iterative refinement and robustness…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Om Govind Jha , Manoj Bamniya , Ayon Borthakur

The Denoising Autoencoder (DAE) enhances the flexibility of the data stream method in exploiting unlabeled samples. Nonetheless, the feasibility of DAE for data stream analytic deserves an in-depth study because it characterizes a fixed…

Machine Learning · Computer Science 2020-01-10 Andri Ashfahani , Mahardhika Pratama , Edwin Lughofer , Yew Soon Ong

Colloidal molecules are ideal model systems for mimicking real molecules and can serve as versatile building blocks for the bottom-up self-assembly of flexible and smart materials. While most colloidal molecules are rigid objects, the…

We study coupled mass transport in a tumor--microenvironment setting with two motile densities $(S,R)$ and non-motile state switching $(P,A)$. The populations diffuse and undergo chemotactic drift; $(P,A)$ follow pointwise ODE switching. A…

Analysis of PDEs · Mathematics 2026-01-29 Jiguang Yu , Louis Shuo Wang , Zonghao Liu , Jingfeng Liu

Using the Colour Glass Condensate description of electron-nucleus collisions at high energy, we study the diffractive production of a pair of jets with transverse momenta much larger than the nuclear saturation momentum $Q_s$. At leading…

High Energy Physics - Phenomenology · Physics 2025-12-15 E. Iancu , D. N. Triantafyllopoulos , S. Y. Wei , F. Yuan

The recent success of large foundation models in artificial intelligence has prompted the emergence of chemical pre-trained models. Despite the growing interest in large molecular pre-trained models that provide informative representations…

Machine Learning · Computer Science 2025-05-26 Jinho Chang , Jong Chul Ye

The kinetic stability of collisionless, sloshing beam-ion (45{\deg} pitch angle) plasma is studied in a 3D simple magnetic mirror, mimicking the Wisconsin High-temperature superconductor Axisymmetric Mirror (WHAM) experiment. The…

Molecular conformation generation, a critical aspect of computational chemistry, involves producing the three-dimensional conformer geometry for a given molecule. Generating molecular conformation via diffusion requires learning to reverse…

Computational Physics · Physics 2023-10-10 Zihan Zhou , Ruiying Liu , Chaolong Ying , Ruimao Zhang , Tianshu Yu

We report a method to convert discrete representations of molecules to and from a multidimensional continuous representation. This model allows us to generate new molecules for efficient exploration and optimization through open-ended…