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Generating a novel and optimized molecule with desired chemical properties is an essential part of the drug discovery process. Failure to meet one of the required properties can frequently lead to failure in a clinical test which is costly.…

Machine Learning · Computer Science 2020-10-28 Bonggun Shin , Sungsoo Park , JinYeong Bak , Joyce C. Ho

Recent research has extended methods from the fields of thermodynamics and statistical mechanics into other disciplines. Most notably, one recent work creates a unified theoretical framework to understand evolutionary biology, machine…

Populations and Evolution · Quantitative Biology 2024-05-22 Daniel Sadasivan , Cole Cantu , Cecilia Marsh , Andrew Graham

Permutation tests are a powerful and flexible approach to inference via resampling. As computational methods become more ubiquitous in the statistics curriculum, use of permutation tests has become more tractable. At the heart of the…

Methodology · Statistics 2025-06-09 Johanna Hardin , Lauren Quesada , Julie Ye , Nicholas J. Horton

We introduce a model of probabilistic verification in mechanism design. The principal elicits a message from the agent and then selects a test to give the agent. The agent's true type determines the probability with which he can pass each…

Theoretical Economics · Economics 2025-01-16 Ian Ball , Deniz Kattwinkel

Machine learning models were shown to be vulnerable to model stealing attacks, which lead to intellectual property infringement. Among other methods, substitute model training is an all-encompassing attack applicable to any machine learning…

Machine Learning · Computer Science 2025-03-11 Daryna Oliynyk , Rudolf Mayer , Andreas Rauber

Language Models (LMs) often cannot be deployed because of their potential to harm users in hard-to-predict ways. Prior work identifies harmful behaviors before deployment by using human annotators to hand-write test cases. However, human…

Computation and Language · Computer Science 2022-02-08 Ethan Perez , Saffron Huang , Francis Song , Trevor Cai , Roman Ring , John Aslanides , Amelia Glaese , Nat McAleese , Geoffrey Irving

Language Generation Models produce words based on the previous context. Although existing methods offer input attributions as explanations for a model's prediction, it is still unclear how prior words affect the model's decision throughout…

Computation and Language · Computer Science 2023-05-23 Javier Ferrando , Gerard I. Gállego , Ioannis Tsiamas , Marta R. Costa-jussà

This work proposes a novel procedure to test for common structures across two high-dimensional factor models. The introduced test allows to uncover whether two factor models are driven by the same loading matrix up to some linear…

Methodology · Statistics 2026-03-17 Marie-Christine Düker , Vladas Pipiras

Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or search-based algorithms. Despite their…

Software Engineering · Computer Science 2022-04-13 Fabiano Pecorelli , Giovanni Grano , Fabio Palomba , Harald C. Gall , Andrea De Lucia

Property-based testing (PBT) is a technique for validating code against an executable specification by automatically generating test-data. We present a proof-theoretical reconstruction of this style of testing for relational specifications…

Logic in Computer Science · Computer Science 2025-01-22 Dale Miller , Alberto Momigliano

This contribution is devoted to a new model of HIV multiplication motivated by the patent of one of the authors. We take into account the antigenic diversity through what we define "antigenicity", whether of the virus or of the adapted…

Numerical Analysis · Mathematics 2011-02-02 François Dubois , Hervé Le Meur , Claude Reiss

In software testing, a set of test cases is constructed according to some predefined selection criteria. The software is then examined against these test cases. Three interesting observations have been made on the current artifacts of…

Software Engineering · Computer Science 2020-03-02 T. Y. Chen , S. C. Cheung , S. M. Yiu

Sampling is a common strategy for generating text from probabilistic models, yet standard ancestral sampling often results in text that is incoherent or ungrammatical. To alleviate this issue, various modifications to a model's sampling…

Computation and Language · Computer Science 2024-01-08 Clara Meister , Tiago Pimentel , Luca Malagutti , Ethan G. Wilcox , Ryan Cotterell

Search-based procedural content generation (PCG) is a well-known method for level generation in games. Its key advantage is that it is generic and able to satisfy functional constraints. However, due to the heavy computational costs to run…

Artificial Intelligence · Computer Science 2022-08-26 Ahmed Khalifa , Michael Cerny Green , Julian Togelius

Consider the problem of imputing missing values in a dataset. One the one hand, conventional approaches using iterative imputation benefit from the simplicity and customizability of learning conditional distributions directly, but suffer…

Machine Learning · Statistics 2022-06-17 Daniel Jarrett , Bogdan Cebere , Tennison Liu , Alicia Curth , Mihaela van der Schaar

Detecting overfitting in generative models is an important challenge in machine learning. In this work, we formalize a form of overfitting that we call {\em{data-copying}} -- where the generative model memorizes and outputs training samples…

Machine Learning · Computer Science 2020-04-14 Casey Meehan , Kamalika Chaudhuri , Sanjoy Dasgupta

In materials science, the challenge of rapid prototyping materials with desired properties often involves extensive experimentation to find suitable microstructures. Additionally, finding microstructures for given properties is typically an…

Machine Learning · Computer Science 2024-05-22 Sébastien Bompas , Stefan Sandfeld

Software testing is a critical, yet resource-intensive phase of the software development lifecycle. Over the years, various automated tools have been developed to aid in this process. Search-based approaches typically achieve high coverage…

Software Engineering · Computer Science 2026-02-11 Pengyu Chang , Yixiong Fang , Silin Chen , Yuling Shi , Beijun Shen , Xiaodong Gu

In this article, we discuss a novel approach to solving number sequence problems, in which sequences of numbers following unstated rules are given, and missing terms are to be inferred. We develop a methodology of decomposing test sequences…

History and Overview · Mathematics 2022-11-29 John Prager

We introduce generative adversarial models in which the discriminator is replaced by a calibrated (non-differentiable) classifier repeatedly enhanced by domain relevant features. The role of the classifier is to prove that the actual and…

Machine Learning · Computer Science 2019-10-08 Shahar Harel , Meir Maor , Amir Ronen