5 papers
Benchmarking the Benchmarks: Evaluating Benchmarks for Conversational Agents
Noam Koren, Roy Bar-Haim, Abigail Goldsteen
Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed. Poor benchmarks may contain inconsi…
SFO: Learning PDE Operators via Spectral Filtering
Noam Koren, Rafael Moschopoulos, Kira Radinsky +1
Partial differential equations (PDEs) govern complex systems, yet neural operators often struggle to efficiently capture the long-range, nonlocal interactions inherent in their sol…
SVD-NO: Learning PDE Solution Operators with SVD Integral Kernels
Noam Koren, Ralf J. J. Mackenbach, Ruud J. G. van Sloun +2
Neural operators have emerged as a promising paradigm for learning solution operators of partial differential equa- tions (PDEs) directly from data. Existing methods, such as those…
Membership Inference Attacks Against Time-Series Models
Noam Koren, Abigail Goldsteen, Guy Amit +1
Analyzing time-series data that contains personal information, particularly in the medical field, presents serious privacy concerns. Sensitive health data from patients is often us…
Interpretable Multivariate Time Series Forecasting Using Neural Fourier Transform
Noam Koren, Kira Radinsky
Multivariate time series forecasting is a pivotal task in several domains, including financial planning, medical diagnostics, and climate science. This paper presents the Neural Fo…