Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball

We present a simple regularization of adversarial perturbations based upon the perceptual loss. While the resulting perturbations remain imperceptible to the human eye, they differ from existing adversarial perturbations in that they are semi-sparse alterations that highlight objects and regions of interest while leaving the background unaltered. As a semantically meaningful adverse perturbations, it forms a bridge between counterfactual explanations and adversarial perturbations in the space of images. We evaluate our approach on several standard explainability benchmarks, namely, weak localization, insertion deletion, and the pointing game demonstrating that perceptually regularized counterfactuals are an effective explanation for image-based classifiers.Comment: CVPR 202

Explaining holistic image regressors and classifiers in urban analytics with plausible counterfactuals

We propose a new form of plausible counterfactual explanation designed to explain the behaviour of computer vision systems used in urban analytics that make predictions based on properties across the entire image, rather than specific regions of it. We illustrate the merits of our approach by explaining computer vision models used to analyse street imagery, which are now widely used in GeoAI and urban analytics. Such explanations are important in urban analytics as researchers and practioners are increasingly reliant on it for decision making. Finally, we perform a user study that demonstrate our approach can be used by non-expert users, who might not be machine learning experts, to be more confident and to better understand the behaviour of image-based classifiers/regressors for street view analysis. Furthermore, the method can potentially be used as an engagement tool to visualise how public spaces can plausibly look like. The limited realism of the counterfactuals is a concern which we hope to improve in the future

Industrial Application of a Partitioning Scheduler to Support Mixed Criticality Systems

The ever-growing complexity of safety-critical control systems continues to require evolution in control system design, architecture and implementation. At the same time the cost of developing such systems must be controlled and importantly quality must be maintained. This paper examines the application of Mixed Criticality System (MCS) research to a DAL-A aircraft engine Full Authority Digital Engine Control (FADEC) system which includes studying porting the control system’s software to a preemptive scheduler from a non-preemptive scheduler. The paper deals with three key challenges as part of the technology transitions. Firstly, how to provide an equivalent level of fault isolation to ARINC 653 without the restriction of strict temporal slicing between criticality levels. Secondly extending the current analysis for Adaptive Mixed Criticality (AMC) scheduling to include the overheads of the system. Finally the development of clustering algorithms that automatically group tasks into larger super-tasks to both reduce overheads whilst ensuring the timing requirements, including the important task transaction requirements, are met

TACO: : An industrial case study of Test Automation for COverage

Timing analysis is an important part of the development of critical real-time systems. It stems from the need to provide evidence on the behaviour of the system, compliance to requirements and timing bounds. The formal testing process is complicated, and includes tests to achieve compliance with certification requirements. Where possible, testing should be performed on a host and then validated on the target. This is especially important for real systems where the target may not be available early in the project or target-based testing is expensive and time consuming. Meaningful host-based testing is difficult when it comes to timing analysis. Automation helps reduce the costs and move testing earlier in the application development cycle. Moving testing earlier in the development cycle not only enables the testing to scale to whole systems, it allows the risks of projects to be managed and software to be optimised before target-based testing is performed. In this paper, we extend existing work achieving reliable coverage and High WaterMark (HWM) measurement, to scale its application to the analysis of a full system software build, automate the test process, and minimise the set of tests deployed on target. Our case study demonstrates the successful application of the approach on a large code base, i.e. an existing controls system software code. The paper ends with a position statement about how this work is instrumental for both future research but also as part of industry practically analysing the timing behaviour of systems automatically and certifying mixed-criticality systems

The Palomar Transient Factory Orion Project: Eclipsing Binaries and Young Stellar Objects

The Palomar Transient Factory (PTF) Orion project is an experiment within the broader PTF survey, a systematic automated exploration of the sky for optical transients. Taking advantage of the wide field of view available using the PTF camera at the Palomar 48" telescope, 40 nights were dedicated in December 2009-January 2010 to perform continuous high-cadence differential photometry on a single field containing the young (7-10Myr) 25 Ori association. The primary motivation for the project is to search for planets around young stars in this region. The unique data set also provides for much ancillary science. In this first paper we describe the survey and data reduction pipeline, and present initial results from an inspection of the most clearly varying stars relating to two of the ancillary science objectives: detection of eclipsing binaries and young stellar objects. We find 82 new eclipsing binary systems, 9 of which we are candidate 25 Ori- or Orion OB1a-association members. Of these, 2 are potential young W UMa type systems. We report on the possible low-mass (M-dwarf primary) eclipsing systems in the sample, which include 6 of the candidate young systems. 45 of the binary systems are close (mainly contact) systems; one shows an orbital period among the shortest known for W UMa binaries, at 0.2156509 \pm 0.0000071d, with flat-bottomed primary eclipses, and a derived distance consistent with membership in the general Orion association. One of the candidate young systems presents an unusual light curve, perhaps representing a semi-detached binary system with an inflated low-mass primary or a star with a warped disk, and may represent an additional young Orion member. Finally, we identify 14 probable new classical T-Tauri stars in our data, along with one previously known (CVSO 35) and one previously reported as a candidate weak-line T-Tauri star (SDSS J052700.12+010136.8).Comment: 66 pages, 27 figures, accepted to Astronomical Journal. Minor typographical corrections and update to author affiliation

Seasonal Arctic sea ice forecasting with probabilistic deep learning.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss

The PTF Orion Project: a Possible Planet Transiting a T-Tauri Star

We report observations of a possible young transiting planet orbiting a previously known weak-lined T-Tauri star in the 7-10 Myr old Orion-OB1a/25-Ori region. The candidate was found as part of the Palomar Transient Factory (PTF) Orion project. It has a photometric transit period of 0.448413 +- 0.000040 days, and appears in both 2009 and 2010 PTF data. Follow-up low-precision radial velocity (RV) observations and adaptive optics imaging suggest that the star is not an eclipsing binary, and that it is unlikely that a background source is blended with the target and mimicking the observed transit. RV observations with the Hobby-Eberly and Keck telescopes yield an RV that has the same period as the photometric event, but is offset in phase from the transit center by approximately -0.22 periods. The amplitude (half range) of the RV variations is 2.4 km/s and is comparable with the expected RV amplitude that stellar spots could induce. The RV curve is likely dominated by stellar spot modulation and provides an upper limit to the projected companion mass of M_p sin i_orb < 4.8 +- 1.2 M_Jup; when combined with the orbital inclination, i orb, of the candidate planet from modeling of the transit light curve, we find an upper limit on the mass of the planetary candidate of M_p < 5.5 +- 1.4 M_Jup. This limit implies that the planet is orbiting close to, if not inside, its Roche limiting orbital radius, so that it may be undergoing active mass loss and evaporation.Comment: Corrected typos, minor clarifications; minor updates/corrections to affiliations and bibliography. 35 pages, 10 figures, 3 tables. Accepted to Ap