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Thinking about the future is thought to play an important role in day to day life, and increasing research indicates that how people think about their own future is related to their mood. For example, how you are feeling may influence how positive or negative the future seems to you, and vice versa....
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This is part 6 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first part: I: Computational Graphs. Part I: Computatio...
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In this video, I give an introduction to the field of computational cognitive modeling in general, and connectionist modeling in particular. We deal with the following topics: The purpose of computational cognitive modeling Where connectionist models fit into the broader picture How connectionist mo...
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This is part 4 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation The last filtering algorithm we are going to dis...
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This is part 3 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation This post deals with another solution to the con...
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In many real-world classification problems, we stumble upon training data with unbalanced classes. This means that the individual classes do not contain the same number of elements. For example, if we want to build an image-based skin cancer detection system using convolutional neural networks, we m...
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This is part 2 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation Idea The Histogram Filter is the most straightfo...
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This is part 1 in a series of tutorials in which we explore methods for robot localization: the problem of tracking the location of a robot over time with noisy sensors and noisy motors, which is an important task for every autonomous robot, including self-driving cars. The methods that we will lear...
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This text deals with arguments against the possibility of so-called strong artificial intelligence, with a particular focus on the Chinese Room Argument devised by philosopher John Searle. We start…
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Introduction This text gives an overview of Gödel’s Incompleteness Theorem and its implications for artificial intelligence. Specifically, we deal with the question whether Gödel’s Incompleteness T…
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In this text, we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicking the TensorFlow API. I …
deepideas.net
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