Tootfinder

City Features VIII 👣
城市特征 VIII 👣
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

The new Deftones record 'Private Music' is DAMN good and worth a listen
Edit - it's on Bandcamp: https://deftonesofficial.bandcamp.com/album/private-music
And YouTube too, if you just wanna do it there:

Small solutions of ternary quadratic congruences with averaging over the moduli
Stephan Baier, Aishik Chattopadhyay
https://arxiv.org/abs/2509.16980 https://

Small solutions of ternary quadratic congruences with averaging over the moduli
In a recent paper, we proved that for any large enough odd modulus $q\in \mathbb{N}$ and fixed $α_2\in \mathbb{N}$ coprime to $q$, the congruence \[ x_1^2+α_2x_2^2+α_3x_3^2\equiv 0 \bmod{q} \] has a solution of $(x_1,x_2,x_3)\in \mathbb{Z}^3$ with $x_3$ coprime to $q$ of height $\max\{|x_1|,|x_2|,|x_3|\}\le q^{11/24+\varepsilon}$ for, in a sense, almost all $α_3$, where $α_3$ runs over the reduced residue classes modulo $q$. Here it was of significance that $1…

🍺 Rice could be key to brewing better non-alcoholic beer
https://arstechnica.com/science/2025/07/rice-could-be-key-to-brewing-better-non-alcoholic-beer/

Rice could be key to brewing better non-alcoholic beer
“It’s time we move beyond outdated perceptions and recognize what rice can offer in creating beer.”…

Many of you already heard about this new algo that's faster than Dijkstra ( #python

Breaking the Sorting Barrier for Directed Single-Source Shortest Paths
We give a deterministic $O(m\log^{2/3}n)$-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition model. This is the first result to break the $O(m+n\log n)$ time bound of Dijkstra's algorithm on sparse graphs, showing that Dijkstra's algorithm is not optimal for SSSP.

RCTDistill: Cross-Modal Knowledge Distillation Framework for Radar-Camera 3D Object Detection with Temporal Fusion
Geonho Bang, Minjae Seong, Jisong Kim, Geunju Baek, Daye Oh, Junhyung Kim, Junho Koh, Jun Won Choi
https://arxiv.org/abs/2509.17712

RCTDistill: Cross-Modal Knowledge Distillation Framework for Radar-Camera 3D Object Detection with Temporal Fusion
Radar-camera fusion methods have emerged as a cost-effective approach for 3D object detection but still lag behind LiDAR-based methods in performance. Recent works have focused on employing temporal fusion and Knowledge Distillation (KD) strategies to overcome these limitations. However, existing approaches have not sufficiently accounted for uncertainties arising from object motion or sensor-specific errors inherent in radar and camera modalities. In this work, we propose RCTDistill, a novel c…

City Features V 🌆
城市特征 V 🌆
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Q&A with Coinbase CEO Brian Armstrong on starting the company, battling North Korean hackers, stablecoin adoption, the GENIUS Act, pro-crypto Congress, and more (John Collison/Cheeky Pint)
https://cheekypint.substack.com/p/coinbase-ceo-brian-armstrong-on-bitcoin…

Coinbase CEO Brian Armstrong on bitcoin going to $1 million, electing a pro-crypto Congress, and Jamie Dimon
Brian Armstrong joins John Collison to talk about what’s happening behind the scenes at Coinbase: battling North Korean hackers, war stories from early scaling, confronting people who won’t use AI to code, Coinbase becoming people’s primary financial account, and why banks are now embracing crypto.

Monotone Circuit Complexity of Matching
Bruno Cavalar, Mika G\"o\"os, Artur Riazanov, Anastasia Sofronova, Dmitry Sokolov
https://arxiv.org/abs/2507.16105

Monotone Circuit Complexity of Matching
We show that the perfect matching function on $n$-vertex graphs requires monotone circuits of size $\smash{2^{n^{Ω(1)}}}$. This improves on the $n^{Ω(\log n)}$ lower bound of Razborov (1985). Our proof uses the standard approximation method together with a new sunflower lemma for matchings.

Multi-perspective monitoring of wildlife and human activities from camera traps and drones with deep learning models
Hao Chen, Fang Qiu, Li An, Douglas Stow, Eve Bohnett, Haitao Lyu, Shuang Tian
https://arxiv.org/abs/2508.15629

Multi-perspective monitoring of wildlife and human activities from camera traps and drones with deep learning models
Wildlife and human activities are key components of landscape systems. Understanding their spatial distribution is essential for evaluating human wildlife interactions and informing effective conservation planning. Multiperspective monitoring of wildlife and human activities by combining camera traps and drone imagery. Capturing the spatial patterns of their distributions, which allows the identification of the overlap of their activity zones and the assessment of the degree of human wildlife c…