V. Roshan Joseph
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View article: Active Learning via Heteroskedastic Rational Kriging
Active Learning via Heteroskedastic Rational Kriging Open
Active learning methods for emulating complex computer models that rely on stationary Gaussian processes tend to produce design points that uniformly fill the entire experimental region, which can be wasteful for functions which vary only …
View article: Robust designs for Gaussian process emulation of computer experiments
Robust designs for Gaussian process emulation of computer experiments Open
We study in this paper two classes of experimental designs, support points and projected support points, which can provide robust and effective emulation of computer experiments with Gaussian processes. These designs have two important pro…
View article: Hard carbon from wood and its constituents: Toward sustainable sodium and potassium-ion battery anodes
Hard carbon from wood and its constituents: Toward sustainable sodium and potassium-ion battery anodes Open
The growing demand for sustainable energy storage solutions necessitates the development of low-cost, environmentally friendly materials. Wood-derived hard carbons (HCs), including those from wood components such as cellulose, lignin and h…
View article: Derailing Non-Answers via Logit Suppression at Output Subspace Boundaries in RLHF-Aligned Language Models
Derailing Non-Answers via Logit Suppression at Output Subspace Boundaries in RLHF-Aligned Language Models Open
We introduce a method to reduce refusal rates of large language models (LLMs) on sensitive content without modifying model weights or prompts. Motivated by the observation that refusals in certain models were often preceded by the specific…
View article: Efficient Active Learning Strategies for Computer Experiments
Efficient Active Learning Strategies for Computer Experiments Open
Active learning in computer experiments aims at allocating resources in an intelligent manner based on the already observed data to satisfy certain objectives such as emulating or optimizing a computationally expensive function. There are …
View article: Accelerated predictions of the sublimation enthalpy of organic materials with machine learning
Accelerated predictions of the sublimation enthalpy of organic materials with machine learning Open
The sublimation enthalpy, , is a key thermodynamic parameter governing the phase transformation of a substance between its solid and gas phases. This transformation is at the core of many important materials' purification, deposition, and …
View article: Discovering the Unknowns: A First Step
Discovering the Unknowns: A First Step Open
This article aims at discovering the unknown variables in the system through data analysis. The main idea is to use the time of data collection as a surrogate variable and try to identify the unknown variables by modeling gradual and sudde…
View article: Hardware-Accelerated Encrypted Execution of General-Purpose Applications
Hardware-Accelerated Encrypted Execution of General-Purpose Applications Open
Fully Homomorphic Encryption (FHE) is a cryptographic method that guarantees the privacy and security of user data during computation. FHE algorithms can perform unlimited arithmetic computations directly on encrypted data without decrypti…
View article: Automated Analysis of Experiments using Hierarchical Garrote
Automated Analysis of Experiments using Hierarchical Garrote Open
In this work, we propose an automatic method for the analysis of experiments that incorporates hierarchical relationships between the experimental variables. We use a modified version of nonnegative garrote method for variable selection wh…
View article: Rational Kriging
Rational Kriging Open
This article proposes a new kriging that has a rational form. It is shown that the generalized least squares estimator of the mean from rational kriging is much more well behaved than that of ordinary kriging. Parameter estimation and unce…
View article: Machine-Guided Discovery of Acrylate Photopolymer Compositions
Machine-Guided Discovery of Acrylate Photopolymer Compositions Open
Additive manufacturing (AM) can be advanced by the diverse characteristics offered by thermoplastic and thermoset polymers and the further benefits of copolymerization. However, the availability of suitable polymeric materials for AM is li…
View article: Factor Importance Ranking and Selection using Total Indices
Factor Importance Ranking and Selection using Total Indices Open
Factor importance measures the impact of each feature on output prediction accuracy. Many existing works focus on the model-based importance, but an important feature in one learning algorithm may hold little significance in another model.…
View article: Rational Kriging
Rational Kriging Open
This article proposes a new kriging that has a rational form. It is shown that the generalized least squares estimate of the mean from rational kriging is much more well behaved than that from ordinary kriging. Parameter estimation and unc…
View article: Enhancing Sample Quality through Minimum Energy Importance Weights
Enhancing Sample Quality through Minimum Energy Importance Weights Open
Importance sampling is a powerful tool for correcting the distributional mismatch in many statistical and machine learning problems, but in practice its performance is limited by the usage of simple proposals whose importance weights can b…
View article: Discovering the Unknowns: A First Step
Discovering the Unknowns: A First Step Open
This article aims at discovering the unknown variables in the system through data analysis. The main idea is to use the time of data collection as a surrogate variable and try to identify the unknown variables by modeling gradual and sudde…
View article: Asset Bundling for Wind Power Forecasting
Asset Bundling for Wind Power Forecasting Open
The growing penetration of intermittent, renewable generation in US power grids, especially wind and solar generation, results in increased operational uncertainty. In that context, accurate forecasts are critical, especially for wind gene…
View article: ArctyrEX : Accelerated Encrypted Execution of General-Purpose Applications
ArctyrEX : Accelerated Encrypted Execution of General-Purpose Applications Open
Fully Homomorphic Encryption (FHE) is a cryptographic method that guarantees the privacy and security of user data during computation. FHE algorithms can perform unlimited arithmetic computations directly on encrypted data without decrypti…
View article: Understanding the Effect of the Long Tail on Neural Network Compression
Understanding the Effect of the Long Tail on Neural Network Compression Open
Network compression is now a mature sub-field of neural network research: over the last decade, significant progress has been made towards reducing the size of models and speeding up inference, while maintaining the classification accuracy…
View article: Sequential Designs for Filling Output Spaces
Sequential Designs for Filling Output Spaces Open
Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input-output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based modelin…
View article: A new framework for the assessment of model probabilities of the different crystal plasticity models for lamellar grains in α+β Titanium alloys
A new framework for the assessment of model probabilities of the different crystal plasticity models for lamellar grains in α+β Titanium alloys Open
This paper presents a novel framework for assessing the relative accuracy of the different slip transfer criterion in modeling the constitutive response of the lamellar morphology grains in Titanium alloys. The main steps involved in t…
View article: Optimizing the configuration of plasma radiation detectors in the presence of uncertain instrument response and inadequate physics
Optimizing the configuration of plasma radiation detectors in the presence of uncertain instrument response and inadequate physics Open
We present a general method for optimizing the configuration of an experimental diagnostic to minimize uncertainty and bias in inferred quantities from experimental data. The method relies on Bayesian inference to sample the posterior usin…
View article: A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling Open
In this work, we propose a novel framework for large-scale Gaussian process (GP) modeling. Contrary to the global, and local approximations proposed in the literature to address the computational bottleneck with exact GP modeling, we emplo…
View article: Sequential Designs for Filling Output Spaces
Sequential Designs for Filling Output Spaces Open
Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input–output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based modelin…
View article: Adaptive Exploration and Optimization of Materials Crystal Structures
Adaptive Exploration and Optimization of Materials Crystal Structures Open
A central problem of materials science is to determine whether a hypothetical material is stable without being synthesized, which is mathematically equivalent to a global optimization problem on a highly non-linear and multi-modal potentia…