Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Cumulative Games: Who is the current player?
Urban Larsson, Reshef Meir, Yair Zick
https://arxiv.org/abs/2005.06326
- Contest Design with Threshold Objectives
Edith Elkind, Abheek Ghosh, Paul W. Goldberg
https://arxiv.org/abs/2109.03179
- Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications
V. Udaya Sankar, Vishisht Srihari Rao, Y. Narahari
https://arxiv.org/abs/2401.05683 https://mastoxiv.page/@arXiv_csGT_bot/111741115483021453
- Charting the Shapes of Stories with Game Theory
Daskalakis, Gemp, Jiang, Leme, Papadimitriou, Piliouras
https://arxiv.org/abs/2412.05747 https://mastoxiv.page/@arXiv_csGT_bot/113627246220336424
- Computing Evolutionarily Stable Strategies in Multiplayer Games
Sam Ganzfried
https://arxiv.org/abs/2511.20859 https://mastoxiv.page/@arXiv_csGT_bot/115620508246637361
- Autodeleveraging: Impossibilities and Optimization
Tarun Chitra
https://arxiv.org/abs/2512.01112 https://mastoxiv.page/@arXiv_csGT_bot/115649040881525135
- Static Pricing Guarantees for Queueing Systems
Jacob Bergquist, Adam N. Elmachtoub
https://arxiv.org/abs/2305.09168 https://mastoxiv.page/@arXiv_csDS_bot/110382625621173269
- Game of arrivals at a two queue network with heterogeneous customer routes
Agniv Bandyopadhyay, Sandeep Juneja
https://arxiv.org/abs/2310.18149 https://mastoxiv.page/@arXiv_csPF_bot/111322112226936579
- Characterization of Priority-Neutral Matching Lattices
Clayton Thomas
https://arxiv.org/abs/2404.02142 https://mastoxiv.page/@arXiv_econTH_bot/112205968984928881
- Seven kinds of equivalent models for generalized coalition logics
Zixuan Chen, Fengkui Ju
https://arxiv.org/abs/2501.05466 https://mastoxiv.page/@arXiv_csLO_bot/113819715349259373
- Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences
Hadi Hosseini, Samarth Khanna, Ronak Singh
https://arxiv.org/abs/2506.04478 https://mastoxiv.page/@arXiv_csAI_bot/114635186215388479
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Den här sköna jazz snurran tar ner dagens statistikångest ett par, fem knäpp på skalan #JohnMartyn
Ok, I’m procrastinating downloading a bunch of vids with yt-dlp and at this point I’m already reaching the tabs limit on this Safari profile
What’d be the best way of downloading a bunch of videos with yt-dlp while still keeping a good control of what failed and what succeeded? (this is basically impossible from its output if you feed it a bunch of links in a single go)
I was wanting a webui I could selfhost and it’d show progress and status for each video it’s downloading (and let me pass custom options to the yt-dlp command, such as filename), but should I just make a script with a for loop for each URL instead?
Series D, Episode 09 - Sand
AVON: I wasn't going to say anything. [The ship is shaken and they are all thrown to the ground.]
SOOLIN: How much more of this can the ship take?
DAYNA: Look, there must be some way to get Tarrant off that planet.
https://blake.torpidity.net/m/409/287…
Scattering in Time-Varying Drude-Lorentz Models
Bryce Dixon, Calvin M. Hooper, Ian R. Hooper, Simon A. R. Horsley
https://arxiv.org/abs/2511.19322 https://arxiv.org/pdf/2511.19322 https://arxiv.org/html/2511.19322
arXiv:2511.19322v1 Announce Type: new
Abstract: Motivated by recent experiments, the theoretical study of wave propagation in time varying materials is of current interest. Although significant in nearly all such experiments, material dispersion is commonly neglected in theoretical studies. Yet, as we show here, understanding the precise microscopic model for the material dispersion is crucial for predicting experimental outcomes. Here we study the temporal scattering coefficients of four different time-varying Drude-Lorentz models, exploring how an incident continuous wave splits into forward and backward waves due to an abrupt change in plasma frequency. The differences in the predicted scattering are unique to time-varying media, and arise from the exact way in which the time variation appears in the various model parameters. We verify our results using a custom finite difference time domain algorithm, concluding with a discussion of the limitations that arise from using these models with an abrupt change in plasma frequency.
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