Tootfinder

"Collaboration instead of academic competition" - my motto for the interview on the recent World Climate Research Program Workshop - "a climate modeling summit" - which we hosted in Hamburg. Find out why I believe so👇
https://www.cliccs.uni-hamburg…

Hamburg Hosts Climate Modelling Summit
The first WCRP-ESMO meeting took place in Hamburg, where Earth System Modelling Scientists talked about their future research. An interview with Professor Tatiana Ilyina.

Enhancing Knowledge Retrieval with Topic Modeling for Knowledge-Grounded Dialogue
Nhat Tran, Diane Litman
https://arxiv.org/abs/2405.04713 https://<…

Enhancing Knowledge Retrieval with Topic Modeling for Knowledge-Grounded Dialogue
Knowledge retrieval is one of the major challenges in building a knowledge-grounded dialogue system. A common method is to use a neural retriever with a distributed approximate nearest-neighbor database to quickly find the relevant knowledge sentences. In this work, we propose an approach that utilizes topic modeling on the knowledge base to further improve retrieval accuracy and as a result, improve response generation. Additionally, we experiment with a large language model, ChatGPT, to take …

Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
Jiuyun Hu, Ziyue Li, Chen Zhang, Fugee Tsung, Hao Yan
https://arxiv.org/abs/2404.04403

Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
Tensor clustering has become an important topic, specifically in spatio-temporal modeling, due to its ability to cluster spatial modes (e.g., stations or road segments) and temporal modes (e.g., time of the day or day of the week). Our motivating example is from subway passenger flow modeling, where similarities between stations are commonly found. However, the challenges lie in the innate high-dimensionality of tensors and also the potential existence of anomalies. This is because the three ta…

Coupling of the Finite Element Method with Physics Informed Neural Networks for the Multi-Fluid Flow Problem
Michel Nohra, Steven Dufour
https://arxiv.org/abs/2405.05371

Coupling of the Finite Element Method with Physics Informed Neural Networks for the Multi-Fluid Flow Problem
Multi-fluid flows are found in various industrial processes, including metal injection molding and 3D printing. The accuracy of multi-fluid flow modeling is determined by how well interfaces and capillary forces are represented. In this paper, the multi-fluid flow problem is discretized using a combination of a Physics-Informed Neural Network (PINN) with a finite element discretization. To determine the best PINN formulation, a comparative study is conducted using a manufactured solution. We co…

Wooden Overcoats 😂😜⚰️
Dramatized comedy series | Total listening time: 21h 36m
Rudyard Funn and his equally miserable sister Antigone run a failing funeral parlour, where they get the body in the coffin in the ground on time. But one day they find a new competitor. With their dogsbody Georgie and a mouse called Madel...
https://w…

Wooden Overcoats 😂😜⚰️
Dramatized comedy series | Total listening time: 21h 36m Rudyard Funn and his equally miserable sister Antigone run a failing funeral parlour, where they get the body in the coffin in the ground on time. But one day they find a new competitor. With their dogsbody Georgie and a mouse called Madeleine, they are taking drastic steps to stay in business... 4 seasons, 34 episodes as of Mar 31, 2022.

This https://arxiv.org/abs/2210.08072 has been replaced.
link: https://scholar.google.com/scholar?q=a

Modeling the Saturation of the Bell Instability using Hybrid Simulations
The nonresonant streaming instability (Bell instability) plays a pivotal role in the acceleration and confinement of cosmic rays (CRs); yet, the exact mechanism responsible for its saturation and the magnitude of the final amplified magnetic field have not been assessed from first-principles. Using a survey of hybrid simulations (with kinetic ions and fluid electrons), we study the evolution of the Bell instability as a function of the parameters of the CR population. We find that, at saturatio…

Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
Beomseok Kang, Harshit Kumar, Minah Lee, Biswadeep Chakraborty, Saibal Mukhopadhyay
https://arxiv.org/abs/2404.06460

Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
Locally interacting dynamical systems, such as epidemic spread, rumor propagation through crowd, and forest fire, exhibit complex global dynamics originated from local, relatively simple, and often stochastic interactions between dynamic elements. Their temporal evolution is often driven by transitions between a finite number of discrete states. Despite significant advancements in predictive modeling through deep learning, such interactions among many elements have rarely explored as a specific…

This https://arxiv.org/abs/2312.13094 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Automated MPI code generation for scalable finite-difference solvers
Partial differential equations (PDEs) are crucial in modelling diverse phenomena across scientific disciplines, including seismic and medical imaging, computational fluid dynamics, image processing, and neural networks. Solving these PDEs on a large scale is an intricate and time-intensive process that demands careful tuning. This paper introduces automated code-generation techniques specifically tailored for distributed memory parallelism (DMP) to solve explicit finite-difference (FD) stencils…

Topological bifurcations in a mean-field game
Ali Akbar Rezaei Lori, Piyush Grover
https://arxiv.org/abs/2405.05473 https://arxiv.org…

Topological bifurcations in a mean-field game
Mean-field games (MFG) provide a statistical physics inspired modeling framework for decision making in large-populations of strategic, non-cooperative agents. Mathematically, these systems consist of a forward-backward in time system of two coupled nonlinear partial differential equations (PDEs), namely the Fokker-Plank and the Hamilton-Jacobi-Bellman equations, governing the agent state and control distribution, respectively. In this work, we study a finite-time MFG with a rich global bifurca…

This https://arxiv.org/abs/2402.09931 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Modeling considerations about a microchannel heat sink
Many computational studies on hotspot microfluidic cooling devices found in the literature rely on simplified assumptions and conventions that do not capture the full complexity of the conjugate thermal problem, such as constant thermophysical fluid properties, radiation and free air convection on the external walls. These assumptions are generally applied to typical microfluidic devices with a large number of microchannels and operating at Reynolds numbers between 100-1000. A one microchannel …