In Search of Lost Domain GeneralizationIshaan GulrajaniDavid Lopez-PazInternational Conference on Learning Representations
2. Reflecting on universal strategies, applied to science (in general) and to the Epilepsies and Neuropsychiatric Comorbidities (in particular), the academic and scientific field of Contemporary Epileptology 3. Defining human functional neuroanatomy and the birth of Neuroscience: From Galen, Leonardo ...
GNNIC: Finding Long-Lost Sibling Functions with Abstract Similarity. NDSS 2024. GNN for static analysis [pdf] Experimental Analyses of the Physical Surveillance Risks in Client-Side Content Scanning. NDSS 2024. Attack client scanning systems [pdf] Attributions for ML-based ICS Anomaly Detection: Fro...
During the training progress, the parameters (mathematical functions) of the neural network are initially set to random values. The loss function is used to estimate the degree of inconsistency between the predicted value and the true value of the model. Next, the output provided by the function...
Volatility spillover between carbon market and related markets in time-frequency domain based on BEKK-GARCH and complex network analysis Yuqiao Lan, Juntao Chen, Zhehao Huang and Yuanqi Zhao 1 Dec 2024 | Energy, Vol. 311 A state-of-the-art analysis on decomposition method for short-term wind...
Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Stran
First, most of the previous findings were based on CT images from a single institute and thus requires generalization testing. The model's performance might be affected by slice spacing that can vary between CT scans in multiple center data. Also, the input data to most of the methods were ...
Due to the school change from Grade 4 to 5, we lost 4.83% of the sample in the second data collection. Thus, our final sample included 532 students (M = 9.72 years, SD = 0.40, range = 9–11; 47% girls), whose socioeconomic status was assessed through their mother/father’s ...
Studying Large Language Model Generalization with Influence Functions;Roger Grosse et al Taken out of context: On measuring situational awareness in LLMs;Lukas Berglund et al OpinionGPT: Modelling Explicit Biases in Instruction-Tuned LLMs;Patrick Haller et al ...
use deep ConvNets with enormous layers and have a very high number of parameters that need to be tuned. Therefore, they demand a huge amount of representative data to improve their performance and generalization ability. While the amount of visual data is increasing exponentially, many of the re...