A typical GAN’s output doesn’t necessarily reflect the data distribution of its training set. Instead, GANs are prone to modeling the majority of the training distribution, sometimes ignoring rare attributes — say, faces that represent minority populations.
Deepfakes have gone mainstream, allowing celebrities to star in commercials without setting foot in a film studio. A new method helps determine whether such endorsements — and other images produced by generative adversarial networks — are authentic.
New research teaches robots to anticipate what’s coming rather than focusing on what’s right in front of them. Researchers developed Occupancy Anticipation (OA), a navigation system that predicts unseen obstacles in addition to observing those in its field of view.
New research teaches robots to anticipate what’s coming rather than focusing on what’s right in front of them. Researchers developed Occupancy Anticipation (OA), a navigation system that predicts unseen obstacles in addition to observing those in its field of view.
As transformer networks move to the fore in applications from language to vision, the time it takes them to crunch longer sequences becomes a more pressing issue. A new method lightens the computational load using sparse attention.
As transformer networks move to the fore in applications from language to vision, the time it takes them to crunch longer sequences becomes a more pressing issue. A new method lightens the computational load using sparse attention.
Two years after it pointed a new direction for language models, Bert still hovers near the top of several natural language processing leaderboards. A new study considers whether Bert simply excels at tracking word order or or learns something closer to common sense.
For people with neurological disorders like epilepsy, attaching sensors to the scalp to measure electrical currents within the brain is benign. But interpreting the resulting electroencephalogram (EEG) graphs can give doctors a headache.
For people with neurological disorders like epilepsy, attaching sensors to the scalp to measure electrical currents within the brain is benign. But interpreting the resulting electroencephalogram (EEG) graphs can give doctors a headache.
Two years after it pointed a new direction for language models, Bert still hovers near the top of several natural language processing leaderboards. A new study considers whether Bert simply excels at tracking word order or or learns something closer to common sense.
Everyone has a favorite optimization method, but it’s not always clear which one works best in a given situation. New research aims to establish a set of benchmarks. Researchers evaluated 14 popular optimizers using the Deep Optimization Benchmark Suite some of them introduced last year.
Large models pretrained in an unsupervised fashion and then fine-tuned on a smaller corpus of labeled data have achieved spectacular results in natural language processing. New research pushes forward with a similar approach to computer vision.
Everyone has a favorite optimization method, but it’s not always clear which one works best in a given situation. New research aims to establish a set of benchmarks. Researchers evaluated 14 popular optimizers using the Deep Optimization Benchmark Suite some of them introduced last year.
Large models pretrained in an unsupervised fashion and then fine-tuned on a smaller corpus of labeled data have achieved spectacular results in natural language processing. New research pushes forward with a similar approach to computer vision.
The technique known as dropout discourages neural networks from overfitting by deterring them from reliance on particular features. A new approach reorganizes the process to run efficiently on the chips that typically run neural network calculations.
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