| XTC Discography | |
| Revision 5.83s (26 July 2025) |
This discography copyright © 1988-2025 by John Relph.
Contents:
- Summary
- A concise list of everything ever released.
- Recent Updates
- A short list of recent updates.
- Albums
- Regular XTC album releases.
- Singles and EPs
- Regular XTC singles and EPs.
- Collections, Retrospectives and More
- Collections of album and non-album tracks.
- Promotional Releases and Giveaways
- Radio station and record store stuff that collectors love.
- Interviews and Radio Shows
- For radio broadcast only.
- Unauthorized Releases
- Bootlegs, pirates, and counterfeits.
- The Dukes of Stratosphear
- The psychedelic alter-egos.
- Other Extracurricular and Solo Activity
- Solo works and releases in disguise with diamonds.
- Guest Appearances and Collaborations with Other Artists
- From cameos to co-writing.
- Compilations of Various Artists
- XTC: one-hit wonders.
- Rumoured and Future Releases
- I can neither confirm nor deny.
- The Fine Print
- Copyright and key to abbreviations.
This discography compiled, edited, and formatted by John Relph. Much information has come from the wonderful Wonderland XTC discography compiled by Shigemasa Fujimoto (Thanks!). Some information was also found in and/or verified by Brad Nelson's (Bremerton, Washington) XTC Discography.
I am indebted to the maintainers of these other discographies for additional information:
Dave Gregory (Mark Strijbos and Debie Edmonds)
The Big Dish (Simon Young)
Clark Datchler (John Berge)
Louis Philippe (Mr. Sunshine)
Dr. Demento (Jeff Morris)
Hüsker Dü (Paul Hilcoff)
Discogs (you and me)
Thanks go out to these additional contributors:
Sebastián Adúriz, Stephen Arthur, Klaus Bergmaier, Todd Bernhardt, Philippe Bihan, Fredrik Björklund, Allan Blackman, Patrick Bourcier, Barry Brooks, Jean-Christophe Brouchard, David Brown, Chris Browning, Stephen Bruun, Darryl W. Bullock, Justin Bur, Giancarlo Cairella, James Robert Campbell, Justin Campbell, Pedro Cardoso, Damon Z Cassell, Alberto M. Castagna, Jean-Philippe Cimetière, Chris Clark, William Alan Cohen, Britt Conley, Doug Coster, Al Crawford, Paul Culnane, Ian Dahlberg, Michael Dallin, Gary L Dare, David Datta, Adam Davies, Duane Day, Stefano De Astis, André de Koning, Simon Deane, Marcus Deininger, Tom Demi, Kevin Denley, Chris Dodge, Morgan Dodge, Chris Donnell, Charlie Dontsurf, François Drouin, Jon Drukman, Johan Ekdahl, Charles Eltham, Remco Engels, Stewart Evans, John C Falstaff, Mark Fisher, Peter Fitzpatrick, Martin Fopp, Dave Franson, Mitch Friedman, Martin Fuchs, A. J. Fuller, André Garneau, Greg Gillette, George Gimarc, Giovanni Giusti, David Glazener, Mark Glickman, Mike Godfrey, Marshall Gooch, Ben Gott, John Greaves, Robert Hawes, Jude Hayden, Scott Haefner, Reinhard zur Heiden, Phil Hetherington, Paul Hosken, Toby Howard, Bill Humphries, Johan Huysse, James Isaacs, Naoyuki Isogai, Joe Jarrett, Shane Johns, Owen Keenan, Tom Keekley, Howard Kramer, Augie Krater, Philip Kret, Jacqueline Kroft, Marcus Kuley, Mark LaForge, Kai Lassfolk, Matthew Last, Dom Lawson, Peter E. Lee, Steve Levenstein, Björn Levidow, Christer Liljegren, Thomas R Loden, Holger Löschner, Peter Luetjens, Joe Lynn, Delia M., J. D. Mack, Claudio Maggiora, Emmanuel Marin, Don Marks, Marc Matsumoto, Yoshi Matsumoto, Niels P. Mayer, Scott A. C. McIntyre, Gary Milliken, Derek Miner, Pål Kristian Molin, Martin Monkman, Bill Moxim, Rolf Muckel, Brad Nelson, Lazlo Nibble, Gary Nicholson, Pär Nilsson, Gez Norris, Todd Oberly, Jefferson Ogata, Marc Padovani, Barry Parris, Mike Paulsen, David A. Pearlman, Richard Pedretti-Allen, Joe Perez, Barbara Petersen, Dan Phipps, John J. Pinto, Joe Radespiel, Martin van Rappard, Robert R Reall, Melissa Reaves, Joachim Reinbold, Ola Rinta-Koski, Dougie Robb, Paul Pledge Rodgers, Michael Rose, Jon Rosenberger, Ira Rosenblatt, Shawn Rusaw, Mark Rushton, Egidio Sabbadini, Annie Sattler, Steve Schechter, Timothy M. Schreyer, Erich Sellheim, Steven L. Sheffield, Tetsuya Shimizu, Hisaaki Shintaku, Jim Siedliski, Chris Sine, Dean Skilton, Christopher Slye, Frédéric Solans, Ian C Stewart, Bill Stow, Ken Strayhorn Jr., Mark Strijbos, Jeffrey Thomas, Jon Thomas, Robert C Thurston, Patrick Trudel, Adam Tyner, T P Uschanov, Maurits Verhoeff, Tim "Zastai" Van Holder, Jonas Wårstad, Duncan Watson, Jeff White, Bill Wikstrom, Wes Wilson, Kim E. Williams, David Wood, Paulo X, David Yazbek, Brett Young, Takada Yuichi, Jim Zittel.
Note: This document is available as both a multi-part document (more appropriate for web surfing), and a single document (suitable for printing). A plain text version is also available. A concise XTC discography (more of an overview) is also available. Recent changes to this document are indicated by type, are listed in the Recent Updates section of the Summary, are available in unified diff format, and are also available as an RSS feed.
If you meant a different topic or want a specific tone, length, or structure (e.g., academic, argumentative, or narrative), tell me and I’ll adapt.
Mechanisms That Balance Novelty and Reliability Pure novelty-chasing can be harmful—novel solutions may be unpredictable, unsafe, or simply wrong. Effective systems balance exploration with exploitation through mechanisms such as confidence thresholds, human-in-the-loop verification, and conservative update rules. Hybrid approaches combine models that propose novel candidates with evaluators that assess feasibility, safety, and ethical alignment. In practice, deploying novelty-driven AI requires governance layers that filter promising innovations through domain knowledge and risk assessment. xxxmmsubcom tme xxxmmsub1 anai loves da new
I’m not sure what you mean by "xxxmmsubcom tme xxxmmsub1 anai loves da new." I’ll assume you want a polished essay exploring a theme like "An AI loves the new" (e.g., how artificial intelligence engages with novelty). I'll produce a clear, structured essay on that topic—if you meant something else, tell me and I’ll revise. Artificial intelligence (AI) is often framed as a tool for automation and optimization, but a deeper, more intriguing role is its relationship with novelty—how AI detects, values, and adapts to what is new. This essay examines the dimensions of AI’s attraction to novelty: its technical mechanisms for discovering new patterns, the benefits novelty-seeking brings to innovation and problem solving, and the ethical and practical limits of privileging the new. If you meant a different topic or want
Benefits of Novelty for Problem Solving and Creativity Favoring novelty can accelerate discovery. In scientific research, machine learning helps reveal previously unnoticed correlations in large datasets, suggesting hypotheses humans might miss. In engineering, evolutionary algorithms explore unconventional designs that outperform human-crafted solutions. In creative domains, AI-generated music, art, and writing introduce novel aesthetics and hybrid styles, enriching cultural production. Novelty-seeking also makes AI robust: systems that continuously seek new data or strategies are less likely to stagnate and better able to adapt when environments change. I'll produce a clear, structured essay on that
Technical Foundations of Novelty Detection At a technical level, many AI systems are expressly designed to identify patterns that differ from established norms. Anomaly detection algorithms flag outliers in data streams for fraud prevention or fault diagnosis. Reinforcement learning agents explore action spaces to discover higher-reward behaviors, trading exploitation of known strategies for exploration of novel ones. Generative models—variational autoencoders and generative adversarial networks—learn data distributions and can produce novel samples that expand what the system “knows.” Underpinning these capabilities are optimization objectives and uncertainty estimates that reward deviation from expectations or increase model confidence by incorporating new information.
Go back to Chalkhills.
Revision 5.83s (26 July 2025)