相关论文: A multi-instance deep neural network classifier: a…
With the development of computational pathology, deep learning methods for Gleason grading through whole slide images (WSIs) have excellent prospects. Since the size of WSIs is extremely large, the image label usually contains only…
In multiple instance learning, objects are sets (bags) of feature vectors (instances) rather than individual feature vectors. In this paper we address the problem of how these bags can best be represented. Two standard approaches are to use…
We conduct a detailed exploration of charged Higgs boson masses $M_{H^{\pm}}$ within the range of $100-190~GeV$. This investigation is grounded in the benchmark points that comply with experimental constraints, allowing us to systematically…
The precise determination of the Higgs boson CP properties is among the most important goals for existing and future colliders. In this work, we evaluate existing constraints on the CP nature of the Higgs interaction with top quarks taking…
We consider the Higgs boson decay processes and its production, and provide a parameterisation tailored for testing models of new physics beyond the Standard Model. We also compare our formalism to other existing parameterisations based on…
Recent work has brought renewed attention to the possibility that the cross section for producing $n$ Higgs bosons grows large with $n$ at a sufficiently energetic hadron collider. In particular, this "Higgsplosion'" mechanism has been…
Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an…
The Helstrom measurement (HM) is known to be the optimal strategy for distinguishing non-orthogonal quantum states with minimum error. Previously, a binary classifier based on classical simulation of the HM has been proposed. It was…
We investigate the potential to detect Higgs boson decays to four bottom quarks through a pair of pseudoscalars, a final state that is predicted by many theories beyond the Standard Model. For the first time, the signal sensitivity is…
The recently discovered scalar resonance at the LHC is now almost confirmed to be a Higgs Boson, whose CP properties are yet to be established. At the ILC with and without polarized beams, it may be possible to probe these properties at…
A reliable determination of the Higgs production mechanism in hadron collider experiments is essential in the program of the measurements of the Higgs couplings. We employ weak supervision, CWoLa in particular, to train deep neural networks…
The sensitivity of the LHC experiments to the Standard Model Higgs using $H\to\tau\tau\to l^+l^-\sla{p_t}$ associated with one high $P_T$ jet in the mass range $110 <M_H<150 \gev$/c$^2$ is investigated. A cut and Neural Network based event…
Binary classification involves predicting the label of an instance based on whether the model score for the positive class exceeds a threshold chosen based on the application requirements (e.g., maximizing recall for a precision bound).…
We present a novel probabilistic programming framework that couples directly to existing large-scale simulators through a cross-platform probabilistic execution protocol, which allows general-purpose inference engines to record and control…
With the ever growing amount of data collected by the ATLAS and CMS experiments at the CERN LHC, fiducial and differential measurements of the Higgs boson production cross section have become important tools to test the standard model…
Signature-based detectors for hyperspectral target detection rely on knowing the specific target signature in advance. However, target signature are often difficult or impossible to obtain. Furthermore, common methods for obtaining target…
In this work we study the production and decay of two CP-even Higgs bosons in the general CP-conserving two-Higgs doublet model at the LHC. We also study the limiting case of the decoupling scenario. For each Yukawa version of the model, we…
Possibilites for measuring the $J^{PC}$ quantum numbers of the Higgs particle through its interactions with gauge bosons and with fermions are discussed. Observables which indicate CP violation in these couplings are also identified.
Information geometry can be used to understand and optimize Higgs measurements at the LHC. The Fisher information encodes the maximum sensitivity of observables to model parameters for a given experiment. Applied to higher-dimensional…
Robust environment perception is essential for decision-making on robots operating in complex domains. Principled treatment of uncertainty sources in a robot's observation model is necessary for accurate mapping and object detection. This…