Node Embedding over Temporal Graphs

In this work, we present a method for node embedding in temporal graphs. We propose an algorithm that learns the evolution of a temporal graph's nodes and edges over time and incorporates this dynamics in a temporal node embedding framework for different graph prediction tasks. We present a joint loss function that creates a temporal embedding of a node by learning to combine its historical temporal embeddings, such that it optimizes per given task (e.g., link prediction). The algorithm is initialized using static node embeddings, which are then aligned over the representations of a node at different time points, and eventually adapted for the given task in a joint optimization. We evaluate the effectiveness of our approach over a variety of temporal graphs for the two fundamental tasks of temporal link prediction and multi-label node classification, comparing to competitive baselines and algorithmic alternatives. Our algorithm shows performance improvements across many of the datasets and baselines and is found particularly effective for graphs that are less cohesive, with a lower clustering coefficient

Origin and early evolution of North American Tapiroidea

North American Eocene tapiroids evolved along two main lines, represented by the families Isectolophidae and Helaletidae….https://elischolar.library.yale.edu/peabody_museum_natural_history_bulletin/1016/thumbnail.jp

The Effect of Diffusion and Concentration of Responsibility on the Risky Shift Phenomenon in a Two-choice Situation

The role of diffusion of responsibility in the production of the risky shift phenomenon was examined in a two-choice situation. Expected value of the two choices was held constant by varying payoffs inversely with their probabilities. After 100 trials alone, subjects were put into one of three conditions for the next 100 trials: Control Condition, Group Diffusion of Responsibility Condition or Group Concentration of Responsibility Condition. No significant shifts were found in any of these conditions. The Kogan and Wallach prediction that diffusion of responsibility would lead to a greater risky shift was not supported. The results were consistent with Zajonc, Wolosin, Wolosin, and Sherman\u27s contention that the utility of being correct produced a conservative shift in the group condition of their experiment. The findings of the present experiment imply that the risky shift phenomenon may not occur under all diffusion of responsibility conditions