Are internet rumours of a comet hurtling towards Earth true? Rumours across social media platforms that a huge comet is on a collision course with Earth have been circulating, with some users describing it as a major threat to humanity. Others are debating how the comet - known as 3I/ATLAS and detected by NASA's ATLAS telescope on July 1 - might be diverted from the Earth. Some have even gone so far as to highlight "news" of military movements and an international coordination to counter the comet before impact, prompting further alarm. So is there any truth to these rumours and what do we know for sure?

We consider the problem of identifying multiway block structure from a large noisy tensor. Such problems arise frequently in applications such as genomics, recommendation system, topic modeling, and sensor network localization.

To solve this, we perform probabilistic reasoning over the depth of neural networks.

Neural Information Processing Systems http://nips.cc/

However, their ability to access and precisely manipulate knowledge is still limited, and hence on knowledge-intensive tasks, their performance lags behind task-specific architectures.

Germany's Munich airport has resumed operations after drone sightings led to the cancellation of 17 flights, the diversion of 15 others and the stranding of some 3,000 passengers. Flights had restarted by early Friday, with flight tracking websites showing planes departing the airport at about 5:50am (03:50 GMT). At least 19 Lufthansa flights were affected, either cancelled or re-routed, because of the airport suspension, the spokesperson added. Earlier, the airport said that drone sightings were first reported by German air traffic control at 10:18pm local time [20:18 GMT] on Thursday, leading initially to a restriction on flights, which was then upgraded to a full suspension. Germany's DPA news agency said police reported that several people had seen a drone near the airport, with later sightings of a drone over the airport grounds.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. This paper addresses the classical problem of unsupervised learning of latent topic model, with an extra variable called response, which can be a score. The main issue is that the topic model (and the embeddings deduced from it) may not help in learning this extra variable, as the response can be induced by phenomena that are orthogonal to the topics. The goal of the so-called supervised topic model learning is to drive the topic learning into a direction which makes it useful w.r.t. the prediction of this extra variable (by a regression). The basic model considered is the Latent Dirichlet allocation (LDA) model.