Augmenting tactic-based interactive theorem provers with neural guidance has been the focus of increased attention in recent years [1, 2, 3, 4, 5]. The dominant approach uses imitation learning on corpora of formalized mathematics. However, despite recent efforts involving self-supervised pre-training [5] or data-augmentation [6], this approach is limited by the conspicuous scarcity of human-producedtrainingdata.

Trump's ominous warning to Colombia as acting Venezuelan president issues message to world calling for'peace and dialogue, not war' Trump plans a military'quarantine' of Venezuela's oil to strong-arm Maduro's successor I got a GLP-1 drug with few questions asked... and never meeting a doctor face-to-face. But could that convenience have put my health at risk? Addicted, arrested and dead in a hotel corridor...Victoria Jones is the latest child of a famous parent to tragically spiral. So why ARE so many children of the rich and famous cursed? Marco Rubio'runs laps' around CBS reporter who asked why US commandos didn't nab Maduro associates in daring night time raid Prince Harry'desperately wants King Charles to come to Montecito and see Archie and Lilibet' Travis Kelce finally addresses possible retirement as Chiefs lose to NFL's worst team in what could be humiliating end to his iconic career State of Jennifer Garner and Jennifer Lopez's relationship revealed by insiders... as parents gossip about'less sociable' star at school play NASA's'queen of diamonds' EXPOSED: Genius is accused of treachery over top secret mission... as chilling details emerge Michael B. Jordan's unimpressed face sends fans wild as Timothee Chalamet cries on stage over Kylie Jenner North West, 12, sparks face piercing speculation after backlash over'risky' body modification'Out-of-touch' Gayle King slammed for complaining that her upper class seat doesn't have a window on her eight-hour flight'back to work' from Hawaii American family of seven stranded after Venezuela raids say they're trapped in a living hell... while oblivious influencers BOAST about getting stuck Ten people who spread false claims France's First Lady Brigitte Macron was born a man are found guilty of cyberbullying in Paris EXPOSED: The Air Force vet who let China steal America's nuclear secrets... and KEPT his $200K tax-funded salary From'sand theft auto' to space BABIES: The global innovations and trends set to shape 2026 From the rise of the humanoid robot to the weird world of AI girlfriends, 2025 had no shortage of strange and transformative inventions. Now, experts from the Nesta research foundation have revealed the global innovations and trends set to shape the world in 2026.

Why Maduro dated wife for TWENTY years before marrying in secret... as shamed first lady's incestuous party links laid bare Maduro's brazen gestures to onlookers as he arrives at rat-infested'hell hole' prison in Brooklyn Trump says Venezuelan opposition leader who beat him to Nobel prize'does not have support' to be president Inside the CIA's astonishing coup of Caracas: SETH HARP reveals the planning... the traitor... and how it's about to blow up in American faces Inside Operation'Absolute Resolve': The meticulous months-long plan to seize Maduro and the harrowing escape under fire Leonardo DiCaprio forced to skip film festival in California by Trump's Venezuela airstrikes as he accepts acting prize via video Inside the glamorous Dubai life of Daniel Kinahan, head of the notorious crime family and Europe's top cocaine kingpin... as GUY ADAMS reveals how net is finally closing in on the gangster after golden decade in the Middle East Explosive warning from America's house price Nostradamus: New forecast tracking over 300 markets reveals'rare' shift... the boomtowns set to sink... and surprising winners I thought I'd found the perfect boyfriend. Then I discovered what he really wanted... Wild moment NYC jeweler attacks'scammer' rival and claims he is impersonating him I'm 38 and hotter than ever after finally silencing food noise with my simple new method... you don't need drugs or diets Meghan McCain, 41, joyously announces birth of third child and reveals baby's unconventional name Female college football fan labeled a Karen for furious reaction to rival in the stands... but was she right all along? Snitch reveals the TRUTH about Tom Brady and Alix Earle... after handsy video leaked out of St Barts The'ideal man' is now a 5'7 architect, dating app analysis reveals READ MORE: Dating apps are designed to keep singles'swiping and spending' The saying goes that'beauty is in the eye of the beholder'. But have you ever wondered what the'perfect' man looks like? Now, just in time for'Dating Sunday' - the busiest day of the year on dating apps - happn has uncovered what the most popular men on its dating app in 2025 look like.

Why Maduro dated wife for TWENTY years before marrying in secret... as shamed first lady's incestuous party links laid bare Maduro's brazen gestures to onlookers as he arrives at rat-infested'hell hole' prison in Brooklyn Brutal Venezuelan dictator Nicolás Maduro dramatically'seized by US as he tried to flee to panic room' Inside the CIA's astonishing coup of Caracas: SETH HARP reveals the planning... the traitor... and how it's about to blow up in American faces Thousands trapped in paradise INDEFINITELY as Trump's Maduro arrest halts all flights to and from 19 Caribbean islands Eagle eyed viewers spot odd detail in background of Trump's Mar-a-Lago war room during Maduro strike in Venezuela Inside the glamorous Dubai life of Daniel Kinahan, head of the notorious crime family and Europe's top cocaine kingpin... as GUY ADAMS reveals how net is finally closing in on the gangster after golden decade in the Middle East Explosive warning from America's house price Nostradamus: New forecast tracking over 300 markets reveals'rare' shift... the boomtowns set to sink... and surprising winners I thought I'd found the perfect boyfriend. Then I discovered what he really wanted... Emergency exit was'always locked', bartender claims amid probe into deadly Swiss ski resort inferno I'm 38 and hotter than ever after finally silencing food noise with my simple new method... you don't need drugs or diets Female college football fan labeled a Karen for furious reaction to rival in the stands... but was she right all along? Meghan McCain, 41, joyously announces birth of third child and reveals baby's unconventional name Snitch reveals the TRUTH about Tom Brady and Alix Earle... after handsy video leaked out of St Barts NFL fans go crazy as Buccaneers player Elijah Roberts' mom crushes national anthem before huge Panthers game Taylor Swift's wedding dress at BFF Este Haim's nuptials has fans spotting secret Easter Egg Today is the busiest day of the YEAR for dating apps - here's the best time to go online If you're hoping to find love in 2026, today could be a good day to get started. January 4 is the busiest day of the year for dating app activity, with the highest number of messages and likes sent. This is largely driven by New Year's resolutions and a desire for fresh starts, leading to huge spikes in users swiping, matching and messaging.

Background. Dengue outbreaks are a major public health issue, with Brazil reporting 71% of global cases in 2024. Purpose. This study aims to describe the profile of severe dengue patients admitted to Brazilian Intensive Care units (ICUs) (2012-2024), assess trends over time, describe new onset complications while in ICU and determine the risk factors at admission to develop complications during ICU stay. Methods. We performed a prospective study of dengue patients from 253 ICUs across 56 hospitals. We used descriptive statistics to describe the dengue ICU population, logistic regression to identify risk factors for complications during the ICU stay, and a machine learning framework to predict the risk of evolving to complications. Visualisations were generated using ISARIC VERTEX. Results. Of 11,047 admissions, 1,117 admissions (10.1%) evolved to complications, including non-invasive (437 admissions) and invasive ventilation (166), vasopressor (364), blood transfusion (353) and renal replacement therapy (103). Age>80 (OR: 3.10, 95% CI: 2.02-4.92), chronic kidney disease (OR: 2.94, 2.22-3.89), liver cirrhosis (OR: 3.65, 1.82-7.04), low platelets (<50,000 cells/mm3; OR: OR: 2.25, 1.89-2.68), and high leukocytes (>7,000 cells/mm3; OR: 2.47, 2.02-3.03) were significant risk factors for complications. A machine learning tool for predicting complications was proposed, showing accurate discrimination and calibration. Conclusion. We described a large cohort of dengue patients admitted to ICUs and identified key risk factors for severe dengue complications, such as advanced age, presence of comorbidities, higher level of leukocytes and lower level of platelets. The proposed prediction tool can be used for early identification and targeted interventions to improve outcomes in dengue-endemic regions.

Automatic language identification is frequently framed as a multi-class classification problem. However, when creating digital corpora for less commonly written languages, it may be more appropriate to consider it a data mining problem. For these varieties, one knows ahead of time that the vast majority of documents are of little interest. By minimizing resources spent on classifying such documents, we can create corpora much faster and with better coverage than using established pipelines. To demonstrate the effectiveness of the language mining perspective, we introduce a new pipeline and corpora for several French-based Creoles.

Drone-based remote sensing combined with AI-driven methodologies has shown great potential for accurate mapping and monitoring of coral reef ecosystems. This study presents a novel multi-scale approach to coral reef monitoring, integrating fine-scale underwater imagery with medium-scale aerial imagery. Underwater images are captured using an Autonomous Surface Vehicle (ASV), while aerial images are acquired with an aerial drone. A transformer-based deep-learning model is trained on underwater images to detect the presence of 31 classes covering various coral morphotypes, associated fauna, and habitats. These predictions serve as annotations for training a second model applied to aerial images. The transfer of information across scales is achieved through a weighted footprint method that accounts for partial overlaps between underwater image footprints and aerial image tiles. The results show that the multi-scale methodology successfully extends fine-scale classification to larger reef areas, achieving a high degree of accuracy in predicting coral morphotypes and associated habitats. The method showed a strong alignment between underwater-derived annotations and ground truth data, reflected by an AUC (Area Under the Curve) score of 0.9251. This shows that the integration of underwater and aerial imagery, supported by deep-learning models, can facilitate scalable and accurate reef assessments. This study demonstrates the potential of combining multi-scale imaging and AI to facilitate the monitoring and conservation of coral reefs. Our approach leverages the strengths of underwater and aerial imagery, ensuring the precision of fine-scale analysis while extending it to cover a broader reef area.

We introduce Monster--the MONash Scalable Time Series E valuation R epository--a collection of large datasets for time series classification. The field of time series classification has benefitted from common benchmarks set by the UCR and UEA time series classification repositories. However, the datasets in these benchmarks are small, with median sizes of 217 and 255 examples, respectively. In consequence they favour a narrow subspace of models that are optimised to achieve low classification error on a wide variety of smaller datasets, that is, models that minimise variance, and give little weight to computational issues such as scalability. Our hope is to diversify the field by introducing benchmarks using larger datasets. We believe that there is enormous potential for new progress in the field by engaging with the theoretical and practical challenges of learning effectively from larger quantities of data.

Data augmentation is a crucial step in the development of robust supervised learning models, especially when dealing with limited datasets. This study explores interpolation techniques for the augmentation of geo-referenced data, with the aim of predicting the presence of Commelina benghalensis L. in sugarcane plots in La R{\'e}union. Given the spatial nature of the data and the high cost of data collection, we evaluated two interpolation approaches: Gaussian processes (GPs) with different kernels and kriging with various variograms. The objectives of this work are threefold: (i) to identify which interpolation methods offer the best predictive performance for various regression algorithms, (ii) to analyze the evolution of performance as a function of the number of observations added, and (iii) to assess the spatial consistency of augmented datasets. The results show that GP-based methods, in particular with combined kernels (GP-COMB), significantly improve the performance of regression algorithms while requiring less additional data. Although kriging shows slightly lower performance, it is distinguished by a more homogeneous spatial coverage, a potential advantage in certain contexts.

Data augmentation is a crucial step in the development of robust supervised learning models, especially when dealing with limited datasets. This study explores interpolation techniques for the augmentation of geo-referenced data, with the aim of predicting the presence of Commelina benghalensis L. in sugarcane plots in La R\'eunion. Given the spatial nature of the data and the high cost of data collection, we evaluated two interpolation approaches: Gaussian processes (GPs) with different kernels and kriging with various variograms. The objectives of this work are threefold: (i) to identify which interpolation methods offer the best predictive performance for various regression algorithms, (ii) to analyze the evolution of performance as a function of the number of observations added, and (iii) to assess the spatial consistency of augmented datasets. The results show that GP-based methods, in particular with combined kernels (GP-COMB), significantly improve the performance of regression algorithms while requiring less additional data. Although kriging shows slightly lower performance, it is distinguished by a more homogeneous spatial coverage, a potential advantage in certain contexts.