Self-exciting Hawkes processes are used to model events which cluster in time and space, and have been widely studied in seismology under the name of the Epidemic Type Aftershock Sequence (ETAS) model. In the ETAS framework, the occurrence of the mainshock earthquakes in a geographical region is assumed to follow an inhomogeneous spatial point process, and aftershock events are then modelled via a separate triggering kernel. Most previous studies of the ETAS model have relied on point estimates of the model parameters due to the complexity of the likelihood function, and the difficulty in estimating an appropriate mainshock distribution. In order to take estimation uncertainty into account, we instead propose a fully Bayesian formulation of the ETAS model which uses a nonparametric Dirichlet process mixture prior to capture the spatial mainshock process. Direct inference for the resulting model is problematic due to the strong correlation of the parameters for the mainshock and triggering processes, so we instead use an auxiliary latent variable routine to perform efficient inference.

Causal inference is a critical research topic across many domains, such as statistics, computer science, education, public policy and economics, for decades. Nowadays, estimating causal effect from observational data has become an appealing research direction owing to the large amount of available data and low budget requirement, compared with randomized controlled trials. Embraced with the rapidly developed machine learning area, various causal effect estimation methods for observational data have sprung up. In this survey, we provide a comprehensive review of causal inference methods under the potential outcome framework, one of the well known causal inference framework. The methods are divided into two categories depending on whether they require all three assumptions of the potential outcome framework or not. For each category, both the traditional statistical methods and the recent machine learning enhanced methods are discussed and compared. The plausible applications of these methods are also presented, including the applications in advertising, recommendation, medicine and so on. Moreover, the commonly used benchmark datasets as well as the open-source codes are also summarized, which facilitate researchers and practitioners to explore, evaluate and apply the causal inference methods.

ABOARD, A U.S. MILITARY AIRCRAFT – The top U.S. commander for the Middle East slipped quietly into Iraq Tuesday, as the Trump administration works to salvage relations with Iraqi leaders and shut down the government's push for an American troop withdrawal. Marine Gen. Frank McKenzie became the most senior U.S. military official to visit since an American drone strike in Baghdad last month killed a top Iranian general, enraging the Iraqis. McKenzie met with Iraq leaders in Baghdad and then went to see American troops at al-Asad Air base, which was bombed by Iran last month in retaliation for the drone attack. Later, he said he was "heartened" by the meetings, adding, "I think we're going to be able to find a way forward." His visit comes amid heightened anti-American sentiment that has fueled violent protests, rocket attacks on the embassy and a vote by the Iraqi parliament pushing for withdrawal of U.S. troops from the country.

The US Department of Defense may have a novel solution for intercepting rogue drones that fly too close to its bases. According to a report from Defense One, the Pentagon has signed a contract with Fortem Technologies to use its brand of'Drone Hunter' to nab unmanned aerial vehicle in midair. The drones reportedly use a mixture of AI and radar to track their targets in the sky and then swoop in near enough to shoot out a net attached to a rope that wraps it up mid-flight. While bases are allowed to use more forceful means of neutralizing enemy drones - namely shooting them out of the sky - one of the major advantages of using a Drone Hunter is that it lowers the risk of dangerous debris that might hurt bystanders in urban areas. 'Drone attacks on the nation's men and women in uniform are increasing.

This illustration provided by the Centers for Disease Control and Prevention in January 2020 shows ... [ ] the 2019 Novel Coronavirus (2019-nCoV). This virus was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. The mysterious coronavirus is spreading at an alarming rate. There have been at least 305 deaths as more than 14,300 persons have been infected. On Thursday, the World Health Organization (WHO) declared the coronavirus a global emergency.

The Army is working to deploy artificial intelligence on the battlefield to detect and classify real-time threats for soldiers in the years to come. The new systems, called the Aided Threat Recognition from Mobile Cooperative and Autonomous Sensors (ATR-MCAS), will scan and classify imagery from sensors that can be mounted on vehicles, aerial coverage and autonomous vehicles that will help soldiers recognize incoming threats. It is a tool that Lt. Col. Chris Lowrance, head of autonomous systems with the Army's AI Task Force, said will act as a "teammate" and reduce "cognitive load" by alerting soldiers of incoming threats. Soldiers in vehicles or holding mobile devices will be able to customize the feed of data that the ATR-MCAS will show and alert them to, Lowrance said. For example, a soldier driving a tank could set a laptop to only display images of enemy tanks when the computer-vision system detects them.

As risks related to cybersecurity and data governance continue to grow and become one of the world's top concerns, technology will become both our …

When the Indian Space Research Organisation (ISRO) sends its first astronaut into space, it won't have to worry about building her a spacesuit. Vyommitra is a half-humanoid robot that ISRO plans to send to space this December during a bid to successfully land an unmanned spacecraft on the moon. In September, the space agency tried--and failed--to touch down on the lunar surface when its Vikram lander experienced a braking problem. If Vikram had landed safely, India would have been the fourth country to land on the moon, following Russia, the U.S., and China. This time around, as part of India's next space mission, Vyommitra will sit in the Gaganyaan spacecraft, which is equipped to fit up to three humans.

The world's tech powers are sending giant sums of money spinning into Canada, but while many see this as a sign of success, others are worried about researchers and intellectual property being swallowed wholesale. The country is in the midst of an artificial intelligence (AI) boom, with Google, Microsoft, Facebook, Huawei and other global heavyweights spending millions or even hundreds of millions of dollars on research hubs in Quebec, Ontario and Alberta. Canadian doors are open – some fear too open. Jim Hinton, an IP lawyer and founder of the Own Innovation consultancy, reckons that more than half of all AI patents in Canada end up being owned by foreign companies. What we need to be doing is getting money out of our ideas ourselves, instead of seeing foreign talent scoop it all up," said Hinton. "Otherwise we'll never have a Canadian champion." The country is home to hundreds of fledgling AI companies, including much-talked-about start-ups like Element AI and Deep Genomics, but they remain relatively small. "They don't have a strong market position yet," Hinton says. Deep learning pioneers such as Yoshua Bengio and Geoffrey Hinton (no relation to Jim) have nurtured top-notch talent in AI in Canada for years, back when AI was an emerging field. But despite Canadian inheriting this brilliant AI lead from the country's AI "godfathers", big foreign players have an unassailable advantage over homegrown efforts, Hinton said. "It's not an easy go for the average company to make a business out of AI.