The paper addresses the classical network tomography problem of inferring local traffic given origin-destination observations. Focussing on large complex public transportation systems, we build a scalable model that exploits input-output information to estimate the unobserved link/station loads and the users path preferences. Based on the reconstruction of the users' travel time distribution, the model is flexible enough to capture possible different path-choice strategies and correlations between users travelling on similar paths at similar times. The corresponding likelihood function is intractable for medium or large-scale networks and we propose two distinct strategies, namely the exact maximum-likelihood inference of an approximate but tractable model and the variational inference of the original intractable model. As an application of our approach, we consider the emblematic case of the London Underground network, where a tap-in/tap-out system tracks the start/exit time and location of all journeys in a day. A set of synthetic simulations and real data provided by Transport For London are used to validate and test the model on the predictions of observable and unobservable quantities.

Technology Engineering World's largest steam locomotive heads out on tour Union Pacific's Big Boy No. 4014 will travel coast-to-coast in commemoration of the semiquincentennial. Breakthroughs, discoveries, and DIY tips sent six days a week. The world's largest operating steam locomotive is hitting the road--or tracks . Union Pacific's Big Boy No. 4014 is heading out on its first coast-to-coast steam tour to celebrate the United States' 250th anniversary . The first leg begins on March 29, when Big Boy and other historical passenger cars from Union Pacific's Heritage Fleet will travel from the locomotive's home base in Cheyenne, Wyoming, west towards California.

An AI crash could bring down the economy. Some in the tech world think that's the price of progress. The tech billionaire Hemant Taneja admits that AI is a bubble. In fact, he welcomes it: "Bubbles are good," Taneja, the CEO of General Catalyst, a venture-capital firm, told me in an email. If AI comes crashing down, it will lead to "some spectacular failures," he said--companies will go under and people will lose their jobs--but that's a price worth paying for "enduring companies that change the world forever."

East Japan Railway has said it will launch a trial in April of a system that uses artificial intelligence to monitor pantographs on trains running on its busy Yamanote Line in Tokyo to detect defects at an early stage. The railway operator, known as JR East, also plans to use drones to inspect overhead wires and other infrastructure, aiming to reduce the time required to resume operations by 30% when transport service disruptions occur due to equipment problems. Cameras to monitor pantographs, which are located on the roof of a train car and connect the carriage to overheard electrical wires, will be installed near Shimbashi, Ebisu, Mejiro and Uguisudani stations in the capital, the company said Tuesday. The AI system will analyze the images in real time, and if damage is detected, it will notify the control room or other relevant sections. Drones will be dispatched later to inspect overhead wires and other equipment, facilitating faster restoration work.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Various items at the Metro Lost & Found office on March 5, 2026. This is read by an automated voice. Please report any issues or inconsistencies here . If you've ever lost something valuable on a Metro bus or train and assumed it was gone forever, take heart: There is a system for reuniting riders with their possessions.

Jean-Paul Thorbjornsen, an Australian man in his mid-30s, with a rural Catholic upbringing, is a founder of THORChain, a blockchain through which users can swap one cryptocurrency for another and earn fees from making those swaps. THORChain is permissionless, so anyone can use it without getting prior approval from a centralized authority. As a decentralized network, the blockchain is built and run by operators located across the globe. During its early days, Thorbjornsen himself hid behind the pseudonym "leena" and used an AI-generated female image as his avatar. But around March 2024, he revealed his true identity as the mind behind the blockchain. If there is a central question around THORChain, it is this: Exactly who is responsible for its operations?

We use the iWildCam version 2.0 released in 2021 as a Examples of train set images can be seen in Figure 14. Random examples from the out-of-distribution test set. Figure 15 shows examples of train set images. Figure 15: Random examples from the ImageNet ILSVRC 2012 challenge train set [37, 11]. The full training set is notably not class balanced, exhibiting a long-tailed distribution (see Figure 16). Figure 17: Random examples from the iNaturalist 2017 challenge train set [46].

Novel categories names:['High_Jump', 'Front_Crawl', 'Pole_V ault', 'Hammer_Throw', All experiments are conducted under the 16-shot setting. An incremental bayesian approach tested on 101 object categories. Conditional prompt learning for vision-language models.