Inference Bear: Inferring Behavior from before and after Snapshots
نویسندگان
چکیده
We present Inference Bear (Inference Based On Before And After Snapshots) which lets users build functional graphical user interfaces by demonstration. Inference Bear is the first Programming By Demonstration system based on the abstract inference engine described in [5]. Among other things, Inference Bear lets you align, center, move, resize, create and delete user interface elements by demonstration. Its most notable feature is that it does not use domain knowledge in its inferencing.
منابع مشابه
Bayesian approach to inference of population structure
Methods of inferring the population structure, its applications in identifying disease models as well as foresighting the physical and mental situation of human beings have been finding ever-increasing importance. In this article, first, motivation and significance of studying the problem of population structure is explained. In the next section, the applications of inference of p...
متن کاملCultural snapshots: Theory and method
Soc Personal Psychol Compass. 2017;11:e12334. https://doi.org/10.1111/spc3.12334 w Abstract Causal influences of culture on cognition are challenging to examine scientifically. We here introduce a method to address this challenge. Cultural snapshots enable scientists to (a) characterize the cultural information commonly and frequently encountered by a collective, (b) examine how such cultural i...
متن کاملInferring Centrality from Network Snapshots
The topology and dynamics of a complex network shape its functionality. However, the topologies of many large-scale networks are either unavailable or incomplete. Without the explicit knowledge of network topology, we show how the data generated from the network dynamics can be utilised to infer the tempo centrality, which is proposed to quantify the influence of nodes in a consensus network. W...
متن کاملInferring dynamic architecture of cellular networks using time series of gene expression, protein and metabolite data
MOTIVATION High-throughput technologies have facilitated the acquisition of large genomics and proteomics datasets. However, these data provide snapshots of cellular behavior, rather than help us reveal causal relations. Here, we propose how these technologies can be utilized to infer the topology and strengths of connections among genes, proteins and metabolites by monitoring time-dependent re...
متن کاملRunning head: INFERRING CAUSAL VARIABLES FROM CONTINUOUS ACTION SEQUENCES 1 Inferring action structure and causal relationships in continuous sequences of human action
In the real world, causal variables do not come pre-identified or occur in isolation, but instead are embedded within a continuous temporal stream of events. A challenge faced by both human learners and machine learning algorithms is identifying subsequences that correspond to the appropriate variables for causal inference. A specific instance of this problem is action segmentation: dividing a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1994