Tootfinder

Edge interventions can mitigate demographic and prestige disparities in the Computer Science coauthorship network
Kate Barnes, Mia Ellis-Einhorn, Carolina Ch\'avez-Ruelas, Nayera Hasan, Mohammad Fanous, Blair D. Sullivan, Sorelle Friedler, Aaron Clauset
https://arxiv.org/abs/2506.04435…

Edge interventions can mitigate demographic and prestige disparities in the Computer Science coauthorship network
Social factors such as demographic traits and institutional prestige structure the creation and dissemination of ideas in academic publishing. One place these effects can be observed is in how central or peripheral a researcher is in the coauthorship network. Here we investigate inequities in network centrality in a hand-collected data set of 5,670 U.S.-based faculty employed in Ph.D.-granting Computer Science departments and their DBLP coauthorship connections. We introduce algorithms for comb…

This https://arxiv.org/abs/2410.00075 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Optimizing Treatment Allocation in the Presence of Interference
In Influence Maximization (IM), the objective is to -- given a budget -- select the optimal set of entities in a network to target with a treatment so as to maximize the total effect. For instance, in marketing, the objective is to target the set of customers that maximizes the total response rate, resulting from both direct treatment effects on targeted customers and indirect, spillover, effects that follow from targeting these customers. Recently, new methods to estimate treatment effects in …

This https://arxiv.org/abs/2404.02497 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Balancing Efficiency and Equity in Classroom Assignment under Endogenous Peer Effects
This paper presents a three-step empirical framework for optimizing classroom assignments under endogenous peer effects, using data from the China Education Panel Survey (CEPS). We design \textit{PeerNN}, a neural network that mimics endogenous network formation as a discrete choice model, generating a friendship-intensity matrix ($Ω$) that captures student popularity. \textbf{Step 2: Estimating Peer Effects.} We measure the peer effect friends' average 6th-grade class rank weighted by $Ω…

This https://arxiv.org/abs/2504.06212 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

NNN: Next-Generation Neural Networks for Marketing Measurement
We present NNN, an experimental Transformer-based neural network approach to marketing measurement. Unlike Marketing Mix Models (MMMs) which rely on scalar inputs and parametric decay functions, NNN uses rich embeddings to capture both quantitative and qualitative aspects of marketing and organic channels (e.g., search queries, ad creatives). This, combined with its attention mechanism, potentially enables NNN to model complex interactions, capture long-term effects, and improve sales attributi…

This https://arxiv.org/abs/2412.12106 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

The Syncytial Mesh Model: A Biophysical Framework for Scale-Dependent Coherence in the Brain
The brain-mesh model introduces a novel three-layered architecture that integrates local and macro-regional connectivity with an underlying, mesh-inspired network layer. This foundational mesh layer, based on metallic mesh structures, spans the entire brain and generates interference patterns, noise, and resonance effects that modulate both local and global neural dynamics. The fused model goes beyond traditional connectivity frameworks by providing a unified explanation for phenomena such as b…

Robust design of bicycle infrastructure networks
https://www.nature.com/articles/s41598-025-99976-9

Robust design of bicycle infrastructure networks - Scientific Reports
Promoting active mobility like cycling relies on the availability of well-connected, high-quality bicycle networks. However, expanding these networks over an extended planning horizon presents one of the most complex challenges in transport science. This complexity arises from the intricate interactions between infrastructure availability and usage, such as network spillover effects and mode choice substitutions. In this paper, we approach the problem from two perspectives: direct optimization …

#NewPaper out: Anne Reichmuth , Kühn I, Schmidt A, Doktor D (2025) Forested Natura 2000 sites under climate change: effects of tree species distribution shifts. Web Ecology 25: 59–89.
We have modelled and analysed the effect of possible tree species distribution shift in Norway spruce (Picea abies), European beech (Fagus sylvatica), and two oak species (Quercus petraea and Quercus robur), considered jointly on forested Natura 2000 sites, an EU-wide conservation area network. The modelling procedure was performed using 3 to 4 bio-climatic variables derived from 26 variables of the EURO-CORDEX Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations for the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 until 2098. Our results reveal a severe decline in Picea within Natura 2000 sites in central Europe and lower elevations and confirm a strong shift towards higher elevations and latitudes. This amounts to an 18 % absolute mean change (−18 % mean loss, 15 % mean gain). Quercus sp. reveal similar results, with 23 % absolute mean change (−23 % loss, 24 % gain) at Natura 2000 sites, whereas Fagus remains stable throughout the model results with 8 % absolute mean change (−7 % loss, 9 % gain). As ecosystems of any type are highly dynamic, climate change can lead to additional severe pressure on statically defined conservation goals and associated management activities.
#biodiversity #ecology #ClimateChange #conservation

Orthogonality-Constrained Deep Instrumental Variable Model for Causal Effect Estimation
Shunxin Yao
https://arxiv.org/abs/2506.02790 https://

Orthogonality-Constrained Deep Instrumental Variable Model for Causal Effect Estimation
OC-DeepIV is a neural network model designed for estimating causal effects. It characterizes heterogeneity by adding interaction features and reduces redundancy through orthogonal constraints. The model includes two feature extractors, one for the instrumental variable Z and the other for the covariate X*. The training process is divided into two stages: the first stage uses the mean squared error (MSE) loss function, and the second stage incorporates orthogonal regularization. Experimental res…

Sensitivity of DC Network Representation for GIC Analysis
Aniruddh Mishra, Arthur K. Barnes, Jose E. Tabarez, Adam Mate
https://arxiv.org/abs/2505.23016 ht…

Sensitivity of DC Network Representation for GIC Analysis
Geomagnetic disturbances are a threat to the reliability and security of our national critical energy infrastructures. These events specifically result in geomagnetically induced currents, which can cause damage to transformers due to magnetic saturation. In order to mitigate these effects, blocker devices must be placed in optimal locations. Finding this placement requires a dc representation of the ac transmission lines, which this paper discusses. Different decisions in this process, includi…

This https://arxiv.org/abs/2504.07932 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Fractional Chern Insulator and Quantum Anomalous Hall Crystal in Twisted MoTe$_2$
Recent experimental advances have uncovered fractional Chern insulators in twisted MoTe$_2$ (tMoTe$_2$) systems, posing significant theoretical challenges in understanding the interaction effects and correlated topological phases. Here, we construct a realistic moiré lattice model tailored for tMoTe$_2$ and conduct investigations using state-of-the-art tensor-network methods. Our ground-state calculations reveal a rich array of interaction- and filling-dependent phases, including the FCI, Cher…

Physiology-Informed Generative Multi-Task Network for Contrast-Free CT Perfusion
Wasif Khan, Kyle B. See, Simon Kato, Ziqian Huang, Amy Lazarte, Kyle Douglas, Xiangyang Lou, Teng J. Peng, Dhanashree Rajderkar, John Rees, Pina Sanelli, Amita Singh, Ibrahim Tuna, Christina A. Wilson, Ruogu Fang
https://arxiv.org/abs/2505.22673

Physiology-Informed Generative Multi-Task Network for Contrast-Free CT Perfusion
Perfusion imaging is extensively utilized to assess hemodynamic status and tissue perfusion in various organs. Computed tomography perfusion (CTP) imaging plays a key role in the early assessment and planning of stroke treatment. While CTP provides essential perfusion parameters to identify abnormal blood flow in the brain, the use of contrast agents in CTP can lead to allergic reactions and adverse side effects, along with costing USD 4.9 billion worldwide in 2022. To address these challenges,…

Geopolitical Tensions and Financial Networks: Strategic Shifts Toward Alternatives
Antonis Ballis
https://arxiv.org/abs/2505.21480 https://

Geopolitical Tensions and Financial Networks: Strategic Shifts Toward Alternatives
Global financial systems are undergoing strategic shifts as geopolitical tensions reshape international trade and payments. The United States (US)-China trade war, sanctions regimes, and rising concerns over the weaponization of financial infrastructures like SWIFT have led countries to seek alternative networks, including China's CIPS and emerging cross-border CBDCs. This letter presents a dynamic theoretical framework where sanction risks, investment choices, and network effects drive payment…