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#Sequence Modeling

Showing: 25 courses
Association for Computing Machinery (ACM)

Deep Learning for Sequences in Quantitative Finance

1 rewiews
Overview of deep learning sequence methods in quantitative finance, covering feature extraction, return forecasting, portfolio allocation, and trading execution. Explores applications and challenges in the investment process.
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24 Lesons
1 hour
On-Demand
Free-Video
Stanford University

Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu

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Explore structured state space models for efficient long sequence modeling across modalities, featuring S4's innovative approach to handling extended dependencies in various data types.
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18 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Stanford University

Stanford Seminar - Decision Transformer: Reinforcement Learning via Sequence Modeling

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Innovative approach to reinforcement learning using sequence modeling and Transformer architecture, offering simplicity and scalability while matching or exceeding state-of-the-art performance in various tasks.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
Simons Institute

Computational Benefits and Limitations of Transformers and State-Space Models

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Explore mechanisms enabling retrieval, copying, and length generalization in language models. Compare Transformers' excellence with LSTM and state-space models' limitations in sequence modeling tasks.
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1 Lesons
51 minutes
On-Demand
Free-Video
Alexander Amini

MIT 6.S191 - Recurrent Neural Networks

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Explore recurrent neural networks, LSTMs, and attention mechanisms for sequence modeling. Learn backpropagation through time, gradient issues, and practical applications in deep learning.
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11 Lesons
45 minutes
On-Demand
Free-Video
Alexander Amini

MIT: Recurrent Neural Networks

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Explore deep sequence modeling with recurrent neural networks, including LSTMs and attention mechanisms. Learn to tackle challenges like vanishing gradients and long-term dependencies in sequence tasks.
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33 Lesons
37 minutes
On-Demand
Free-Video
Alexander Amini

Sequence Modeling with Neural Networks

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Explore sequence modeling with neural networks, focusing on RNNs, their challenges, and solutions like gated cells. Learn applications in music generation and machine translation.
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23 Lesons
27 minutes
On-Demand
Free-Video
AI Institute at UofSC - #AIISC

Transformers in Time Series: A Survey

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Explore the application of Transformer models in time series analysis, covering recent advancements and potential future directions in this rapidly evolving field.
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1 Lesons
43 minutes
On-Demand
Free-Video
DataLearning@ICL

Autoregressive Long-Context Music Generation with Perceiver AR

0 rewiews
Explore autoregressive long-context music generation using Perceiver AR, presented by DeepMind's Cătălina Cangea. Gain insights into cutting-edge AI techniques for creating music.
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1 Lesons
1 hour
On-Demand
Free-Video
Discover AI

Mamba AI: Understanding Selective State Space Models as Transformer Alternatives

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Explore the groundbreaking MAMBA architecture and its potential to revolutionize AI through selective state space models, offering a compelling alternative to traditional transformers.
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1 Lesons
46 minutes
On-Demand
Free-Video
The Full Stack

Recurrent Neural Networks - Full Stack Deep Learning - Spring 2021

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Explore Recurrent Neural Networks: architecture, challenges, solutions, and applications. Dive into LSTMs, bidirectionality, attention mechanisms, CTC loss, and non-recurrent sequence models like WaveNet.
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9 Lesons
1 hour 6 minutes
On-Demand
Free-Video
Yannic Kilcher

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

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Explore Mamba, a novel linear-time sequence modeling architecture using selective state spaces. Learn about its advantages over Transformers and its applications in language, audio, and genomics.
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10 Lesons
41 minutes
On-Demand
Free-Video
Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning? - Paper Explained

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Exploring how pre-training on Wikipedia improves offline reinforcement learning models, enhancing performance, reducing parameters, and revealing connections between language and RL domains.
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8 Lesons
39 minutes
On-Demand
Free-Video
Yannic Kilcher

Infinite Memory Transformer - Research Paper Explained

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Explores innovative Transformer model with unbounded memory, enabling processing of arbitrarily long sequences. Discusses continuous attention mechanisms, sticky memories, and potential applications in language modeling.
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11 Lesons
37 minutes
On-Demand
Free-Video
Alexander Amini

Recurrent Neural Networks, Transformers, and Attention

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Explore recurrent neural networks, transformers, and attention mechanisms in deep learning. Learn design principles, applications, and advanced concepts like LSTM and backpropagation through time.
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19 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Yannic Kilcher

Retentive Network - A Successor to Transformer for Large Language Models

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Explores Retentive Network as an alternative to Transformer, offering training parallelism and efficient inference for large language models. Discusses retention mechanism, computation paradigms, and experimental results.
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7 Lesons
28 minutes
On-Demand
Free-Video
Yannic Kilcher

Decision Transformer - Reinforcement Learning via Sequence Modeling

0 rewiews
Explore how Decision Transformer reframes offline reinforcement learning as sequence modeling, leveraging Transformer architecture to generate optimal actions based on desired returns, past states, and actions.
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13 Lesons
57 minutes
On-Demand
Free-Video
Simons Institute

Integrating Constraints into Deep Learning Architectures with Structured Layers

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Explore integrating constraints into deep learning using structured layers, covering deep equilibrium models, implicit layers, and weight-tied networks for enhanced architecture design.
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20 Lesons
50 minutes
On-Demand
Free-Video
WeAreDevelopers

Getting Personal - Deep Learning Methods for Large Scale Personalization

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Explore deep learning methods for large-scale personalization, covering sequence modeling, computer vision, and practical applications in this insightful talk by Noa Barbiro.
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14 Lesons
29 minutes
On-Demand
Free-Video
Alexander Amini

Recurrent Neural Networks and Transformers

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Comprehensive exploration of recurrent neural networks, LSTMs, and attention mechanisms in deep learning, covering theory, implementation, and applications for sequence modeling tasks.
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19 Lesons
58 minutes
On-Demand
Free-Video
Unify

Elastic Decision Transformer Explained

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Explore cutting-edge Elastic Decision Transformer, combining transformers and reinforcement learning. Learn how it enhances traditional models by adaptively modifying historical context during inference.
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1 Lesons
53 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Unraveling Long Context: Existing Methods, Challenges, and Future Directions

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Explore the complexities of scaling transformer models for longer context, examining current methodologies, implementation hurdles, and emerging solutions in AI development.
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1 Lesons
32 minutes
On-Demand
Free-Video
Google TechTalks

Accelerating Transformers via Kernel Density Estimation - Google TechTalk

0 rewiews
Explore efficient Transformer acceleration using kernel density estimation. Learn innovative techniques for handling long sequences and improving performance in deep learning models.
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13 Lesons
53 minutes
On-Demand
Free-Video
Alexander Amini

MIT 6.S191 - Recurrent Neural Networks

0 rewiews
Comprehensive lecture on Recurrent Neural Networks, covering theory, implementation, and applications. Explores sequence modeling, LSTM, attention mechanisms, and practical examples in deep learning.
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15 Lesons
1 hour 1 minute
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Toward Length Extrapolatable Transformers

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Explore innovative techniques for enhancing transformer models' ability to handle longer sequences, improving their performance and scalability in natural language processing tasks.
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1 Lesons
1 hour 5 minutes
On-Demand
Free-Video