21 papers · ranked by Valyu relevance
Oscar Delaney, Sambhav Maheshwari, Joe O'Brien, Theo Bearman + 1 more
Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a possible public release. For example, Anthropic recently developed a new class of model with advanced cyberoffense-relevant capabilities, Mythos Preview, which was…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Kengo Inutsuka, Tadaaki Nishioka, Tom Macpherson, Mana Fujiwara + 2 more
When and how does insight emerge? We conceptualize insight as a sudden realization arising from restructuring a world model: an internal interpretation linking actions to outcomes. Yet these latent dynamics remain difficult to access, even with behavior and verbal report. Here we developed inside insight dynamics…
Bei Qing Huang, Yixin Chen, Ruijie Lu, Gang Zeng + 3 more
We propose GaussianFluent to enable realistic simulation of dynamic scenes, particularly material fracture, within the 3DGS framework. The overall framework is shown in Figure 3. Our method first generates internal structures and textures for GS representations, followed by simulating fracture dynamics using an…
Authors not listed
Supervised deep learning has become a standard approach to deliver competitive predictive tools that allow relating the structure of molecules and their physicochemical features to properties such as binding to protein targets, performance as electronic materials, and reactivity. However, efforts to understand how…
Jie Lu, Zeyu Zheng, Max Langtry, Monty Jackson + 6 more
Title: Summary Building energy modeling is critical for retrofit design, but it is labor-intensive. We present Data2BEM (Data to Building Energy Model), a large language model-based multi-agent framework that parses architectural drawings, specifications, and sensor data to automatically generate and calibrate building…
Sheng Han, Zhiqiang Wang, Yuchen Tang, Li Huang + 3 more
Accurate monitoring of internal winding temperature is essential for assessing the thermal state and operational reliability of oil-immersed transformers. However, direct deployment of distributed temperature sensors inside transformer windings is difficult because of insulation constraints, structural complexity, and…
Authors not listed
We present graphRC, a graph-based method for rapid transition state (TS) mode analysis that provides chemical insight along normal mode displacements and reaction coordinate trajectories by translating Cartesian displacements into meaningful internal coordinate changes. Internal coordinates are constructed using…
Aaron L. Brown, Lei Shi, Matteo Salvador, Fanwei Kong + 4 more
We present a computational framework for constructing patient-specific models of cardiac mechanics based on standard clinical data, including electrocardiogram (ECG), cuff blood pressure, and electrocardiography-gated computed tomography angiography (CTA) imaging. The model is coupled to a closed-loop lumped parameter…
Wenbo Xu, Shenchi Cheng, Chenxi Wu, Chen Li + 5 more
Background Cardiac arrest-associated acute kidney injury is common after cardiac arrest and adversely affects patient survival and disease outcomes. Early prediction of acute kidney injury is essential for guiding clinical management, especially in cardiac arrest patients admitted to the intensive care unit. Early…
Lenard Dome, Frank H. Hezemans, Kenza Kadri, Ben J. Wagner + 3 more
The Computational Psychiatry Modelling (cpm) toolbox is a Python library for theory-driven modelling in computational psychiatry and cognitive (neuro-)science. cpm integrates a wide range of established approaches into a single framework. It is designed to be accessible to both expert and non-expert modellers in order…
Zoe Lee-Youngzie, Naotsugu Tsuchiya, Michael Robinson, Donna Dietz + 4 more
Recent work in the structural approach to consciousness has shown great promise as a research paradigm for the formal and empirical study of the phenomenal qualities of experience, i.e., qualia. In this paradigm, qualia are characterized by modeling the internal organization of parts within an experience, or by…
Li Zhetao, Zeng Xiyu, Wang Jianhui, Xiao Yong + 5 more
While the primary function of computers lies in computation and processing, the core value of the Internet is rooted in sharing and collaboration. Computers create the Internet, and the Internet empowers the value of computers. The rapid development of the Internet, cloud computing, and big data is pushing artificial…
Authors not listed
High-entropy layered double hydroxides (HE-LDHs) have shown great potential in oxygen evolution reaction (OER) catalysis due to their tunable compositions and electronic structures. However, the synergistic effects between multiple vacancies, such as metal and oxygen vacancies, remain poorly understood and challenging…
Raheleh Biglari, Joachim Denil
Model validity is as critical as the model itself, especially when guiding decisionmaking processes. Traditional approaches often rely on predefined validity frames, which may not always be available or sufficient. This paper introduces the Decision Oriented Technique (DOTechnique), a novel method for determining model…
Sergi Picó Cabiró, Alberto Zingaro, Violeta Puche García, Dimitrios Lialios + 6 more
Atrial electromechanics plays a key role in cardiac function by regulating ventricular filling and global hemodynamics, yet remains challenging to model consistently across scales. In this work, a multiscale atrial digital twin for simulations of normal and pathological atrial function is presented, formulated as an…
Authors not listed
Meta-GGA density functional theory (DFT) is an important method in ab initio materials modelling; however, its computational cost limits applicability for generating large datasets or simulating extended length and time scales, as necessary for modern materials discovery. Deorbitalization is a promising strategy to…
Sriram Nagaraj, Advaith Nila Narayanan
As financial institutions transition from traditional predictive models to autonomous agentic systems, the static model inventory requirements of traditional model risk management (MRM) face structural obsolescence. This paper proposes a dynamic Inventory-as-Code (IaC) governance loop that treats the model inventory as…
Authors not listed
Pharmacophores are widely used to describe protein-ligand interactions, and the Grids of Pharmacophore Interaction Fields (GRAIL) method extends this concept by representing binding pockets as interpretable sets of interaction type-specific pharmacophoric maps. In this work, we propose a hybrid framework for binding…
Yangkexin Li, Henry Sun, Zuoli Zhang, Beom Soo Shin
Background: Physiologically based pharmacokinetic (PBPK) modeling is a mathematical approach that integrates human physiological parameters with drug-specific characteristics (including both active pharmaceutical ingredients and excipients), and it has emerged as one of the core technologies for optimizing the…
Authors not listed
For decades, molecular visualization software has been fundamental to education and research in chemistry, structural biology, and materials science. These tools have enabled the inspection of structures, dynamics, and interactions, yet their reliance on two-dimensional (2D) interfaces imposes persistent limitations.…